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| Verfasst von: | Farr, Elias [VerfasserIn]  |
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| | Dimitrov, Daniel [VerfasserIn] |
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| | Schmidt, Christina [VerfasserIn] |
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| | Türei, Dénes [VerfasserIn] |
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| | Lobentanzer, Sebastian [VerfasserIn] |
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| | Dugourd, Aurélien [VerfasserIn] |
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| | Sáez Rodríguez, Julio [VerfasserIn] |
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| Titel: | MetalinksDB |
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| Titelzusatz: | a flexible and contextualizable resource of metabolite-protein interactions |
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| Verf.angabe: | Elias Farr, Daniel Dimitrov, Christina Schmidt, Denes Turei, Sebastian Lobentanzer, Aurelien Dugourd, Julio Saez-Rodriguez |
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| E-Jahr: | 2024 |
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| Jahr: | July 2024 |
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| Umfang: | 12 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Veröffentlicht: 22. Juli 2024 ; Gesehen am 28.04.2025 |
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| Titel Quelle: | Enthalten in: Briefings in bioinformatics |
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| Ort Quelle: | Oxford [u.a.] : Oxford University Press, 2000 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 25(2024), 4 vom: Juli, Seite bbae347$p1-12 |
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| ISSN Quelle: | 1477-4054 |
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| Abstract: | From the catalytic breakdown of nutrients to signaling, interactions between metabolites and proteins play an essential role in cellular function. An important case is cell-cell communication, where metabolites, secreted into the microenvironment, initiate signaling cascades by binding to intra- or extracellular receptors of neighboring cells. Protein-protein cell-cell communication interactions are routinely predicted from transcriptomic data. However, inferring metabolite-mediated intercellular signaling remains challenging, partially due to the limited size of intercellular prior knowledge resources focused on metabolites. Here, we leverage knowledge-graph infrastructure to integrate generalistic metabolite-protein with curated metabolite-receptor resources to create MetalinksDB. MetalinksDB is an order of magnitude larger than existing metabolite-receptor resources and can be tailored to specific biological contexts, such as diseases, pathways, or tissue/cellular locations. We demonstrate MetalinksDB’s utility in identifying deregulated processes in renal cancer using multi-omics bulk data. Furthermore, we infer metabolite-driven intercellular signaling in acute kidney injury using spatial transcriptomics data. MetalinksDB is a comprehensive and customizable database of intercellular metabolite-protein interactions, accessible via a web interface (https://metalinks.omnipathdb.org/) and programmatically as a knowledge graph (https://github.com/biocypher/metalinks). We anticipate that by enabling diverse analyses tailored to specific biological contexts, MetalinksDB will facilitate the discovery of disease-relevant metabolite-mediated intercellular signaling processes. |
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| DOI: | doi:10.1093/bib/bbae347 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1093/bib/bbae347 |
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| | DOI: https://doi.org/10.1093/bib/bbae347 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| K10plus-PPN: | 1923753940 |
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| Verknüpfungen: | → Zeitschrift |
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