Title Systematic analyses of lipid mobilization by human lipid transfer proteins
Authors Titeca, Kevin ; Chiapparino, Antonella ; Hennrich, Marco L ; Türei, Dénes ; Moqadam, Mahmoud ; Talandashti, Reza ; Cuveillier, Camille ; van Ek, Larissa ; Zukowska, Joanna ; Triana, Sergio ; Echelard, Florian ; Nielsen, Inger Ødum ; Foged, Mads Møller ; Gehin, Charlotte ; Olechnovič, Kliment ; Grudinin, Sergei ; Saez-Rodriguez, Julio ; Alexandrov, Theodore ; Maeda, Kenji ; Reuter, Nathalie ; Gavin, Anne-Claude
DOI 10.1038/s41586-025-10040-y
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Is Part of Nature.. Springer Nature. 2026, vol. 651, p. 511-520.. ISSN 0028-0836. eISSN 1476-4687
Abstract [eng] Lipid transfer proteins (LTPs) maintain the specialized lipid compositions of organellar membranes1,2. In humans, many LTPs are implicated in diseases3, but the cargo and auxiliary lipids that facilitate the transfer of the majority of LTPs remain unknown. Here we combined biochemical, lipidomic and computational methods to systematically characterize LTP–lipid complexes4 and measure how LTP gains of function affect cellular lipidomes. We identified bound lipids for around half of the hundreds of LTPs that we analysed, confirming known ligands and identifying new ones across most LTP families. Gains in LTP function affected the cellular abundance of both their known and newly identified lipid ligands, indicating comparable functional relevance of the two ligand sets. Using structural bioinformatics, we characterized mechanisms that contribute to lipid selectivity and identified preferences based on headgroup or acyl chain. We demonstrate some basic principles of how LTPs mobilize their ligands. They commonly interact with several classes of lipids and exhibit broad but selective preference for particular headgroups and for lipid species with shorter acyl chains that contain one or two unsaturated carbons, suggesting that only subsets of lipid species are efficiently mobilized. The datasets represent a resource for further analysis in different cell types and states, such as those associated with pathologies.
Published Springer Nature
Type Journal article
Language English
Publication date 2026
CC license CC license description