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
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.
St. Anna Children's Cancer Research Institute, Vienna, Austria.
Mol Syst Biol. 2025 May 12. doi: 10.1038/s44320-025-00108-2.
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.
人类溶质载体(SLC)超家族包含约460种膜转运蛋白,尽管具有治疗潜力,但仍是研究最少的蛋白家族。为推动SLC研究,我们开发了一个综合知识库,将系统的多组学数据集与从公共来源精选的信息整合在一起。我们通过文献整理注释了SLC底物,使用数据挖掘技术汇编了SLC疾病关联,并通过将公共数据库的注释与免疫荧光成像方法相结合来确定SLC的亚细胞定位。通过一个具有交互式仪表板和可视化工具的门户网站,科学界可以访问这些以SLC为中心的知识。利用这个系统收集和整理的资源,我们通过计算得出了整个人类SLC超家族的综合功能图谱。我们识别出具有不同特性的簇,并确定了转运蛋白之间的功能距离。基于所有可用数据集及其整合,我们为每个SLC赋予了生化/生物学功能,使本研究成为人类基因功能最大规模的系统注释之一,也是未来研究工作的潜在蓝图。