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

  • Datos identificativos

    Identificador: imarina:6178122
    Autores:
    Frainay, ClementSchymanski, Emma LNeumann, SteffenMerlet, BenjaminSalek, Reza MJourdan, FabienYanes, 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:

    Autor según el artículo: Frainay, Clement; Schymanski, Emma L; Neumann, Steffen; Merlet, Benjamin; Salek, Reza M; Jourdan, Fabien; Yanes, Oscar
    Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
    Autor/es de la URV: Yanes Torrado, Óscar
    Palabras clave: 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
    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.
    Áreas temáticas: Molecular biology Medicina ii Farmacia Endocrinology, diabetes and metabolism Ciências biológicas ii Ciências biológicas i Biotecnología Biochemistry & molecular biology Biochemistry
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 22181989
    Direcció de correo del autor: oscar.yanes@urv.cat
    Identificador del autor: 0000-0003-3695-7157
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/2218-1989/8/3/51
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Metabolites. 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
    DOI del artículo: 10.3390/metabo8030051
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2018
    Tipo de publicación: Journal Publications
  • Palabras clave:

    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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