Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

Mind the Gap: Mapping Mass Spectral Databases in Genome-Scale Metabolic Networks Reveals Poorly Covered Areas

  • Identification data

    Identifier: imarina:6178122
  • Authors:

    Frainay, Clement
    Schymanski, Emma L.
    Neumann, Steffen
    Merlet, Benjamin
    Salek, Reza M.
    Jourdan, Fabien
    Yanes, Oscar
  • Others:

    Author, as appears in the article.: Frainay, Clement; Schymanski, Emma L.; Neumann, Steffen; Merlet, Benjamin; Salek, Reza M.; Jourdan, Fabien; Yanes, Oscar;
    Department: Enginyeria Electrònica, Elèctrica i Automàtica
    URV's Author/s: Yanes Torrado, Óscar
    Keywords: Tool Spectrometry Resource Pubchem Metlin Metabolomics data mapping Metabolite annotation Metabolic networks Mass spectral libraries Hmdb Chemical information Annotation metabolite annotation metabolic networks mass spectral libraries
    Abstract: The use of mass spectrometry-based metabolomics to study human, plant and microbial biochemistry and their interactions with the environment largely depends on the ability to annotate metabolite structures by matching mass spectral features of the measured metabolites to curated spectra of reference standards. While reference databases for metabolomics now provide information for hundreds of thousands of compounds, barely 5% of these known small molecules have experimental data from pure standards. Remarkably, it is still unknown how well existing mass spectral libraries cover the biochemical landscape of prokaryotic and eukaryotic organisms. To address this issue, we have investigated the coverage of 38 genome-scale metabolic networks by public and commercial mass spectral databases, and found that on average only 40% of nodes in metabolic networks could be mapped by mass spectral information from standards. Next, we deciphered computationally which parts of the human metabolic network are poorly covered by mass spectral libraries, revealing gaps in the eicosanoids, vitamins and bile acid metabolism. Finally, our network topology analysis based on the betweenness centrality of metabolites revealed the top 20 most important metabolites that, if added to MS databases, may facilitate human metabolome characterization in the future.
    Thematic Areas: Molecular biology Medicina ii Farmacia Endocrinology, diabetes and metabolism Ciências biológicas ii Ciências biológicas i Biotecnología Biochemistry & molecular biology Biochemistry
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 22181989
    Author's mail: oscar.yanes@urv.cat
    Author identifier: 0000-0003-3695-7157
    Record's date: 2023-02-19
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.mdpi.com/2218-1989/8/3/51
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Metabolites. 8 (3):
    APA: Frainay, Clement; Schymanski, Emma L.; Neumann, Steffen; Merlet, Benjamin; Salek, Reza M.; Jourdan, Fabien; Yanes, Oscar; (2018). Mind the Gap: Mapping Mass Spectral Databases in Genome-Scale Metabolic Networks Reveals Poorly Covered Areas. Metabolites, 8(3), -. DOI: 10.3390/metabo8030051
    Article's DOI: 10.3390/metabo8030051
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2018
    Publication Type: Journal Publications
  • Keywords:

    Biochemistry,Biochemistry & Molecular Biology,Endocrinology, Diabetes and Metabolism,Molecular Biology
    Tool
    Spectrometry
    Resource
    Pubchem
    Metlin
    Metabolomics data mapping
    Metabolite annotation
    Metabolic networks
    Mass spectral libraries
    Hmdb
    Chemical information
    Annotation
    metabolite annotation
    metabolic networks
    mass spectral libraries
    Molecular biology
    Medicina ii
    Farmacia
    Endocrinology, diabetes and metabolism
    Ciências biológicas ii
    Ciências biológicas i
    Biotecnología
    Biochemistry & molecular biology
    Biochemistry
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