VPS13A is an intracellular lipid transfer protein comprising over 3,000 amino acids. Mutations in human VPS13A cause VPS13A disease, a neurodegenerative disorder that affects movement and cognition. VPS13A forms a complex with the membrane protein XK to mediate ATP-induced phospholipid scrambling in the plasma membrane. Here, we established a mouse cell system expressing full-length mouse VPS13A and examined its interaction with XK. Mutational analysis revealed that VPS13A binds to XK through a C-terminal β-strand that interacts with a β-hairpin in the central region of XK, an interaction essential for scramblase activity. The XK paralog XKR2, which contains a similar β-hairpin structure, also associates with VPS13A and supports phospholipid scrambling. We analyzed ten mouse VPS13A variants corresponding to patient mutations and classified them into four groups: (1) L67P, I90K, and W2453R, which showed reduced expression; (2) A1091P and M3080R, which were normally expressed but lacked scramblase activity; (3) S1446P, Q2689H, Y2713C, and R3084H, which modestly impaired expression or activity; and (4) I2763R, which altered cell size, and disrupted ER independently of XK. These findings define the VPS13A–XK interaction interface, clarify the functional impact of disease-causing mutations, and reveal an unexpected gain-of-function mutation of a VPS13A variant.
Xing Lin, Yuta Ryoden, Chigure Suzuki, Hiroyuki Ishikawa, Takaharu Sakuragi, Yasuo Uchiyama, Shigekazu Nagata
Usage data is cumulative from March 2026 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 651 | 0 |
| 329 | 0 | |
| Supplemental data | 125 | 0 |
| Citation downloads | 77 | 0 |
| Totals | 1,182 | 0 |
| Total Views | 1,182 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.