# In situ architecture of the lipid transport protein VPS13C at ER–lysosome membrane contacts

Article · Shujun Cai, Yumei Wu, Andrés Guillén-Samander, William F. Hancock-Cerutti, Jun Liu, Pietro V. De Camilli

- Archive id: doi:10.1073/pnas.2203769119
- Published: 2022-07-13
- Venue: Proceedings of the National Academy of Sciences
- DOI: https://doi.org/10.1073/pnas.2203769119
- PMID: 35858323
- PMCID: PMC9303930
- Citations: 106
- Source URL: https://doi.org/10.1073/pnas.2203769119
- PDF: https://europepmc.org/articles/PMC9303930/pdf
- Provenance: openalex+europepmc

## Abstract

VPS13 is a eukaryotic lipid transport protein localized at membrane contact sites. Previous studies suggested that it may transfer lipids between adjacent bilayers by a bridge-like mechanism. Direct evidence for this hypothesis from a full-length structure and from electron microscopy (EM) studies in situ is still missing, however. Here, we have capitalized on AlphaFold predictions to complement the structural information already available about VPS13 and to generate a full-length model of human VPS13C, the Parkinson's disease-linked VPS13 paralog localized at contacts between the endoplasmic reticulum (ER) and endo/lysosomes. Such a model predicts an ∼30-nm rod with a hydrophobic groove that extends throughout its length. We further investigated whether such a structure can be observed in situ at ER-endo/lysosome contacts. To this aim, we combined genetic approaches with cryo-focused ion beam (cryo-FIB) milling and cryo-electron tomography (cryo-ET) to examine HeLa cells overexpressing this protein (either full length or with an internal truncation) along with VAP, its anchoring binding partner at the ER. Using these methods, we identified rod-like densities that span the space separating the two adjacent membranes and that match the predicted structures of either full-length VPS13C or its shorter truncated mutant, thus providing in situ evidence for a bridge model of VPS13 in lipid transport.

_Abstract reproduced under CC-BY (publisher license, via OpenAlex)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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