Literature DB >> 16808440

MET-IDEA: data extraction tool for mass spectrometry-based metabolomics.

Corey D Broeckling1, Indira R Reddy, Anthony L Duran, Xuechun Zhao, Lloyd W Sumner.   

Abstract

A current and significant limitation to metabolomics is the large-scale, high-throughput conversion of raw chromatographically coupled mass spectrometry datasets into organized data matrices necessary for further statistical processing and data visualization. This article describes a new data extraction tool, MET-IDEA (Metabolomics Ion-based Data Extraction Algorithm) which surmounts this void. MET-IDEA is compatible with a diversity of chromatographically coupled mass spectrometry systems, generates an output similar to traditional quantification methods, utilizes the sensitivity and selectivity associated with selected ion quantification, and greatly reduces the time and effort necessary to obtain large-scale organized datasets by several orders of magnitude. The functionality of MET-IDEA is illustrated using metabolomics data obtained for elicited cell culture exudates from the model legume, Medicago truncatula. The results indicate that MET-IDEA is capable of rapidly extracting semiquantitative data from raw data files, which allows for more rapid biological insight. MET-IDEA is freely available to academic users upon request.

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Year:  2006        PMID: 16808440     DOI: 10.1021/ac0521596

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  74 in total

1.  Soybean metabolites regulated in root hairs in response to the symbiotic bacterium Bradyrhizobium japonicum.

Authors:  Laurent Brechenmacher; Zhentian Lei; Marc Libault; Seth Findley; Masayuki Sugawara; Michael J Sadowsky; Lloyd W Sumner; Gary Stacey
Journal:  Plant Physiol       Date:  2010-06-09       Impact factor: 8.340

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.  Combining genetic diversity, informatics and metabolomics to facilitate annotation of plant gene function.

Authors:  Takayuki Tohge; Alisdair R Fernie
Journal:  Nat Protoc       Date:  2010-06-10       Impact factor: 13.491

4.  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

5.  Root exudates regulate soil fungal community composition and diversity.

Authors:  Corey D Broeckling; Amanda K Broz; Joy Bergelson; Daniel K Manter; Jorge M Vivanco
Journal:  Appl Environ Microbiol       Date:  2007-12-14       Impact factor: 4.792

Review 6.  Metabolomics: moving to the clinic.

Authors:  Anders Nordström; Rolf Lewensohn
Journal:  J Neuroimmune Pharmacol       Date:  2009-04-28       Impact factor: 4.147

7.  The future of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discovery.

Authors:  Thomas O Metz; Qibin Zhang; Jason S Page; Yufeng Shen; Stephen J Callister; Jon M Jacobs; Richard D Smith
Journal:  Biomark Med       Date:  2007-06       Impact factor: 2.851

8.  A regulatory network-based approach dissects late maturation processes related to the acquisition of desiccation tolerance and longevity of Medicago truncatula seeds.

Authors:  Jerome Verdier; David Lalanne; Sandra Pelletier; Ivone Torres-Jerez; Karima Righetti; Kaustav Bandyopadhyay; Olivier Leprince; Emilie Chatelain; Benoit Ly Vu; Jerome Gouzy; Pascal Gamas; Michael K Udvardi; Julia Buitink
Journal:  Plant Physiol       Date:  2013-08-08       Impact factor: 8.340

9.  Metabolic rates associated with membrane fatty acids in mice selected for increased maximal metabolic rate.

Authors:  Bernard W M Wone; Edward R Donovan; John C Cushman; Jack P Hayes
Journal:  Comp Biochem Physiol A Mol Integr Physiol       Date:  2013-02-16       Impact factor: 2.320

Review 10.  Opening up the "Black Box": metabolic phenotyping and metabolome-wide association studies in epidemiology.

Authors:  Magda Bictash; Timothy M Ebbels; Queenie Chan; Ruey Leng Loo; Ivan K S Yap; Ian J Brown; Maria de Iorio; Martha L Daviglus; Elaine Holmes; Jeremiah Stamler; Jeremy K Nicholson; Paul Elliott
Journal:  J Clin Epidemiol       Date:  2010-01-08       Impact factor: 6.437

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