Articles producció científicaEnginyeria Electrònica, Elèctrica i Automàtica

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

  • Datos identificativos

    Identificador:  imarina:6178122
    Autores:  Frainay, Clement; Schymanski, Emma L; Neumann, Steffen; Merlet, Benjamin; Salek, Reza M; Jourdan, Fabien; Yanes, Oscar
    Resumen:
    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.
  • Otros:

    Enlace a la fuente original: https://www.mdpi.com/2218-1989/8/3/51
    Referencia de l'ítem segons les normes 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), 51-. DOI: 10.3390/metabo8030051
    Referencia al articulo segun fuente origial: Metabolites. 8 (3): 51-
    DOI del artículo: 10.3390/metabo8030051
    Año de publicación de la revista: 2018
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2024-10-12
    Autor/es de la URV: Yanes Torrado, Óscar
    Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    ISSN: 22181989
    Autor según el artículo: Frainay, Clement; Schymanski, Emma L; Neumann, Steffen; Merlet, Benjamin; Salek, Reza M; Jourdan, Fabien; Yanes, Oscar
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Molecular biology, Medicina ii, Farmacia, Endocrinology, diabetes and metabolism, Ciências biológicas ii, Ciências biológicas i, Biotecnología, Biochemistry & molecular biology, Biochemistry
    Direcció de correo del autor: oscar.yanes@urv.cat
  • Palabras clave:

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