Systematic analyses of lipid mobilization by human lipid transfer proteins
TL;DR
This study systematically analyzes human lipid transfer proteins (LTPs) to identify bound lipids and mechanisms of lipid selectivity. It reveals that LTPs commonly interact with multiple lipid classes, preferring specific head groups and shorter acyl chains with unsaturations. The findings provide a resource for understanding LTP functions in health and disease.
Key Takeaways
- •Identified bound lipids for about half of the hundred LTPs analyzed, confirming known ligands and discovering new ones across most LTP families.
- •Gains in LTP function affected cellular abundance of both known and newly identified lipid ligands, indicating comparable functional relevance.
- •Characterized lipid selectivity mechanisms, showing preferences for specific head groups and lipid species with shorter acyl chains containing unsaturations.
- •Demonstrated that LTPs commonly interact with several lipid classes, exhibiting broad but selective preferences, suggesting only subsets of lipid species are efficiently mobilized.
- •The datasets serve as a resource for further analysis in different cell types and states, including pathological conditions.
Tags
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.
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
A set of gene knockouts as a resource for global lipidomic changes
Uncovering the prevalence, key biogenesis enzymes, and biological significance of archaeal lipoproteins
Evidence for a trap-and-flip mechanism in a proton-dependent lipid transporter
Author information
Antonella Chiapparino
Present address: AB Sciex Germany GmbH, <City>, Germany
Marco L. Hennrich
Present address: Absea Biotechnology GmbH Berlin, Berlin, Germany
Reza Talandashti
Present address: Department of Biochemistry, University of Oxford, Oxford, UK
Sergio Triana
Present address: Institute for Medical Engineering and Science (IMES) and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
Sergio Triana
Present address: Broad Institute of MIT and Harvard, Cambridge, MA, USA
Charlotte Gehin
Present address: École Polytechnique Fédérale de Lausanne (EPFL), <City>, Switzerland
Theodore Alexandrov
Present address: Department of Pharmacology, University of California San Diego, La Jolla, CA, USA
Theodore Alexandrov
Present address: DeepCyte Inc., San Diego, CA, USA
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
European Molecular Biology Laboratory, EMBL, Heidelberg, Germany
Kevin Titeca, Antonella Chiapparino, Marco L. Hennrich, Joanna Zukowska, Sergio Triana, Charlotte Gehin & Theodore Alexandrov
Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, and Heidelberg University Hospital, Heidelberg, Germany
Dénes Türei & Julio Saez-Rodriguez
Department of Chemistry, University of Bergen, Bergen, Norway
Mahmoud Moqadam, Reza Talandashti, Florian Echelard & Nathalie Reuter
Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
Mahmoud Moqadam, Reza Talandashti, Florian Echelard & Nathalie Reuter
Cell Death and Metabolism group, Center for Autophagy, Recycling and Disease, Danish Cancer Institute, Copenhagen, Denmark
Inger Ødum Nielsen, Mads Møller Foged & Kenji Maeda
Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
Kliment Olechnovic
CNRS, Grenoble INP, LJK, Université Grenoble Alpes, Grenoble, France
Kliment Olechnovic & Sergei Grudinin
EMBL European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
Julio Saez-Rodriguez
- Kevin Titeca
Search author on:PubMed Google Scholar
- Antonella Chiapparino
Search author on:PubMed Google Scholar
- Marco L. Hennrich
Search author on:PubMed Google Scholar
- Dénes Türei
Search author on:PubMed Google Scholar
- Mahmoud Moqadam
Search author on:PubMed Google Scholar
- Reza Talandashti
Search author on:PubMed Google Scholar
- Camille Cuveillier
Search author on:PubMed Google Scholar
- s