For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
120
views
50
references
 Top references
cited by
19
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      201
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Spectral Deconvolution for Gas Chromatography Mass Spectrometry-Based Metabolomics: Current Status and Future Perspectives

      review-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Mass spectrometry coupled to gas chromatography (GC-MS) has been widely applied in the field of metabolomics. Success of this application has benefited greatly from computational workflows that process the complex raw mass spectrometry data and extract the qualitative and quantitative information of metabolites. Among the computational algorithms within a workflow, deconvolution is critical since it reconstructs a pure mass spectrum for each component that the mass spectrometer observes. Based on the pure spectrum, the corresponding component can be eventually identified and quantified. Deconvolution is challenging due to the existence of co-elution. In this review, we focus on progress that has been made in the development of deconvolution algorithms and provide thoughts on future developments that will expand the application of GC-MS in metabolomics.

          Related collections

          Most cited references50

          • Record: found
          • Abstract: found
          • Article: not found

          MassBank: a public repository for sharing mass spectral data for life sciences.

          Hisayuki Horai, Masanori Arita, Shigehiko Kanaya … (2010)
          MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data. 2010 John Wiley & Sons, Ltd.
          Article 0 comments Cited 688 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Metabolomics--the link between genotypes and phenotypes.

            Oliver Fiehn (2002)
            Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms 'transcriptome' and proteome', the set of metabolites synthesized by a biological system constitute its 'metabolome'. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.
            Article 0 comments Cited 636 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              METLIN: a metabolite mass spectral database.

              Colin A Smith, Grace O'Maille, Elizabeth J. Want … (2005)
              Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.
              Article 0 comments Cited 512 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Comput Struct Biotechnol J
                Journal ID (iso-abbrev): Comput Struct Biotechnol J
                Journal ID (publisher-id): CSBJ
                Title: Computational and Structural Biotechnology Journal
                Publisher: Research Network of Computational and Structural Biotechnology (RNCSB) Organization
                ISSN (Electronic): 2001-0370
                Publication date (Electronic): 28 June 2013
                Publication date Collection: 2013
                Volume: 4
                Electronic Location Identifier: e201301013
                Affiliations
                [a ]Department of Bioinformatics, University of North Carolina at Charlotte, Charlotte, NC, United States
                [b ]Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
                Author notes
                Citation
                Du X, Zeisel SH (2013) Spectral Deconvolution for Gas Chromatography Mass Spectrometry-Based Metabolomics: Current Status and Future Perspectives. Computational and Structural Biotechnology Journal. 4 (5): e201301013. doi: http://dx.doi.org/10.5936/csbj.201301013
                [* ]Corresponding author: Tel.: +1 7042505754. E-mail address: xiuxia.du@ 123456uncc.edu (Xiuxia Du)
                Article
                Publisher ID: CSBJ-4-e201301013
                DOI: 10.5936/csbj.201301013
                PMC ID: 3962095
                PubMed ID: 24688694
                SO-VID: 0e04376d-e49a-47c8-80bd-dde1c6ac2b0e
                Copyright © © Du and Zeisel.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited.

                History
                Date received : 19 October 2012
                Date revision received : 20 June 2013
                Date accepted : 23 June 2013
                Categories
                Subject: Mini Reviews

                Keywords: metabolomics,mass spectrometry,bioinformatics
                Data availability:
                Keywords: metabolomics, mass spectrometry, bioinformatics

                Comments

                Comment on this article

                scite_

                Similar content201

                See all similar

                Cited by19

                See all cited by

                Most referenced authors991

                See all reference authors