Data- and knowledge-derived functional landscape of human solute carriers

The human solute carrier (SLC) superfamily of ~460 membrane transporters remains the largest understudied protein family despite its therapeutic potential. To advance SLC research, we developed a comprehensive knowledgebase that integrates systematic multi-omics data sets with selected curated infor...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Molecular systems biology Jg. 21; H. 6; S. 599 - 631
Hauptverfasser: Goldmann, Ulrich, Wiedmer, Tabea, Garofoli, Andrea, Sedlyarov, Vitaly, Bichler, Manuel, Haladik, Ben, Wolf, Gernot, Christodoulaki, Eirini, Ingles-Prieto, Alvaro, Ferrada, Evandro, Frommelt, Fabian, Teoh, Shao Thing, Leippe, Philipp, Onea, Gabriel, Pfeifer, Martin, Kohlbrenner, Mariah, Chang, Lena, Selzer, Paul, Reinhardt, Jürgen, Digles, Daniela, Ecker, Gerhard F, Osthushenrich, Tanja, MacNamara, Aidan, Malarstig, Anders, Hepworth, David, Superti-Furga, Giulio
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 02.06.2025
Springer Nature
Schlagworte:
ISSN:1744-4292, 1744-4292
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The human solute carrier (SLC) superfamily of ~460 membrane transporters remains the largest understudied protein family despite its therapeutic potential. To advance SLC research, we developed a comprehensive knowledgebase that integrates systematic multi-omics data sets with selected curated information from public sources. We annotated SLC substrates through literature curation, compiled SLC disease associations using data mining techniques, and determined the subcellular localization of SLCs by combining annotations from public databases with an immunofluorescence imaging approach. This SLC-centric knowledge is made accessible to the scientific community via a web portal featuring interactive dashboards and visualization tools. Utilizing this systematically collected and curated resource, we computationally derived an integrated functional landscape for the entire human SLC superfamily. We identified clusters with distinct properties and established functional distances between transporters. Based on all available data sets and their integration, we assigned biochemical/biological functions to each SLC, making this study one of the largest systematic annotations of human gene function and a potential blueprint for future research endeavors. Synopsis A comprehensive knowledgebase on the 464 human solute carrier (SLC) transporters has been established. It consolidates basic annotations, systematic multi-omics data sets, and curated information from the public domain. This resource is accessible to the scientific community at https://re-solute.eu . A literature-based annotation effort has assigned 468 distinct substrates to 329 SLCs, enabling a substrate-based classification of the transporters. Extensive data mining has linked 780 disease terms to 228 SLCs, providing an overview of the current knowledge of SLC genetics and its impact on human pathophysiology. Analysis of public databases and results from immunofluorescence imaging experiments indicate subcellular localization for 418 SLCs. A novel data integration approach has generated a functional landscape for human SLCs, defining 11 clusters and establishing functional distances between the transporters. Interactive dashboards for data exploration are available at https://re-solute.eu/resources/dashboards , and a web tool for SLC-tree visualizations can be found at https://re-solute.eu/resources/dashboards/slctree . A comprehensive knowledgebase on the 464 human solute carrier (SLC) transporters has been established. It consolidates basic annotations, systematic multi-omics data sets, and curated information from the public domain. This resource is accessible to the scientific community at https://re-solute.eu .
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1744-4292
1744-4292
DOI:10.1038/s44320-025-00108-2