Abstract

Lipid transfer proteins (LTPs) maintain the specialized lipid compositions of organellar membranes1,2. In humans, many LTPs are implicated in diseases3, but for the majority, the cargo and auxiliary lipids facilitating transfer remain unknown. We have 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 approximately half of the hundred LTPs analyzed, confirming known ligands, while discovering 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 have characterized mechanisms contributing to lipid selectivity, identifying preferences based on head group or acyl chain. We demonstrate some basic principles of how LTPs mobilise their ligands. They commonly interact with several classes of lipids and exhibit broad but selective preference, not only for particular head groups, but also for lipid species with shorter acyl chains containing one or two unsaturations, 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.

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Author information

Author notes

Antonella Chiapparino

Present address: AB Sciex Germany GmbH, <City>, Germany 1.

Marco L. Hennrich

Present address: Absea Biotechnology GmbH Berlin, Berlin, Germany 1.

Reza Talandashti

Present address: Department of Biochemistry, University of Oxford, Oxford, UK 1.

Sergio Triana

Present address: Institute for Medical Engineering and Science (IMES) and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA 1.

Sergio Triana

Present address: Broad Institute of MIT and Harvard, Cambridge, MA, USA 1.

Charlotte Gehin

Present address: École Polytechnique Fédérale de Lausanne (EPFL), <City>, Switzerland 1.

Theodore Alexandrov

Present address: Department of Pharmacology, University of California San Diego, La Jolla, CA, USA 1.

Theodore Alexandrov

Present address: DeepCyte Inc., San Diego, CA, USA 1.

These authors contributed equally: Kevin Titeca, Antonella Chiapparino, Marco L. Hennrich

Authors and Affiliations

Department of Cell Physiology and Metabolism, University of Geneva, Geneva, Switzerland

Kevin Titeca, Camille Cuveillier, Larissa van Ek & Anne-Claude Gavin 1.

European Molecular Biology Laboratory, EMBL, Heidelberg, Germany

Kevin Titeca, Antonella Chiapparino, Marco L. Hennrich, Joanna Zukowska, Sergio Triana, Charlotte Gehin & Theodore Alexandrov 1.

Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, and Heidelberg University Hospital, Heidelberg, Germany

Dénes Türei & Julio Saez-Rodriguez 1.

Department of Chemistry, University of Bergen, Bergen, Norway

Mahmoud Moqadam, Reza Talandashti, Florian Echelard & Nathalie Reuter 1.

Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway

Mahmoud Moqadam, Reza Talandashti, Florian Echelard & Nathalie Reuter 1.

Cell Death and Metabolism group, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, Copenhagen, Denmark

Inger Ødum Nielsen, Mads Møller Foged & Kenji Maeda 1.

Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania

Kliment Olechnovic 1.

CNRS, Grenoble INP, LJK, Université Grenoble Alpes, Grenoble, France

Kliment Olechnovic & Sergei Grudinin 1.

EMBL European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK

Julio Saez-Rodriguez

Authors

1. Kevin Titeca
2. Antonella Chiapparino
3. Marco L. Hennrich
4. Dénes Türei
5. Mahmoud Moqadam
6. Reza Talandashti
7. Camille Cuveillier
8. Larissa van Ek
9. Joanna Zukowska
10. Sergio Triana
11. Florian Echelard
12. Inger Ødum Nielsen
13. Mads Møller Foged
14. Charlotte Gehin
15. Kliment Olechnovic
16. Sergei Grudinin
17. Julio Saez-Rodriguez
18. Theodore Alexandrov
19. Kenji Maeda
20. Nathalie Reuter
21. Anne-Claude Gavin

Corresponding authors

Correspondence to Marco L. Hennrich or Anne-Claude Gavin.

Supplementary information

Supplementary Information

This file contains Supplementary Figs. 1–4, Supplementary Tables 12–15, Methods and References.

Reporting Summary

Supplementary Table 1

Molecular Biology Data (Fig. 1a). Table 1A: Primers used for cloning and sequencing results. Table 1B: Sequencing results for LTPs covered in the in cellulo screen.

Supplementary Table 2

Expression and purification of each LTP in HEK293 cells (Fig. 1a).

Supplementary Table 3

Description of MS fragmentation behaviour of lipids with the applied mass spectrometry methods.

Supplementary Table 4

Lipid species associated with LTPs (Figs 3a, 3b, 4a, 4b, 5a and 5c; Extended Data Figs 1c, 1d, 2b and 8a).

Supplementary Table 5

Lipid subclasses associated with LTPs in cellulo and in vitro (Fig. 2a). Table 5A: Normalized MS-intensities from the in cellulo screen. Table 5B: Normalized MS-intensities from the in vitro screen. Table 5C: Table describing if an LTP-lipid interaction is novel or known.

Supplementary Table 6

List of LTPs expressed in in cellulo and in vitro assays, but lipidated in only one of the assays.

Supplementary Table 7

Results of the structural and functional benchmarks. Table 7A: Volumes of LTP lipid binding pockets and volume of their respective ligand lipid species (Figs 1b and 1c; Extended Data Figs 2a, 2c and 2d). Table 7B: Lipidomics data of HEK293 overexpressing and or not an LTP. Table 7C: Changes in lipid species abundance upon individual LTP overexpression (Fig. 1d and 2b). Table 7D: Changes in lipid species upon individual LTP overexpression (Fig. 4b). Results from the paired two-sided t-test of the induced versus non-induced samples. Table 7E: Results of the fluorescence-based binding assay of CERT lipid transfer domain (CERT-STAT), STARD4 and STARD10 to NBD-phosphatidylcholine (Fig. 2d).

Supplementary Table 8

Overview on the novelty of LTP-lipid interactions and their validation experiments.

Supplementary Table 9

Functional relationship of lipids co-mobilized by the same LTP. Table 9A: Manders co-occurrence data for lipid species in the organelles of cells (Extended Data Fig. 6c). Table 9B: Results of the Fisher exact tests for the co-regulation and co-localization analysis (Extended Data Figs 6a, 6b and 6c).

Supplementary Table 10

Lipidomics of liver / brain extracts and of HEK293 cells. Table 10A: Lipid species identified in lipid extracts from liver or brain that were used in the in vitro screen (liposomes) (Figs 4a, 4b, 5a and 5c; Extended Data Fig. 8a). Table 10B: Lipidomics results from HEK293 cells on the lipid species level (Figs 4a, 4b, 5a and 5c; Extended Data Fig. 8a).

Supplementary Table 11

Lipidomics results of HeLa cells over-expressing or not CERT (Extended Data Fig. 7a).

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Titeca, K., Chiapparino, A., Hennrich, M.L. et al. Systematic analyses of lipid mobilization by human lipid transfer proteins. Nature (2026). https://doi.org/10.1038/s41586-025-10040-y

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Received: 12 January 2024

Accepted: 11 December 2025

Published: 07 January 2026

DOI: https://doi.org/10.1038/s41586-025-10040-y