VPS13A and VPS13C influence lipid droplet abundance is a research paper. On theSindex it has a DataRank of 0.285. It has been cited 3 times, with 3 citing works in its 1-hop citation network.
ABSTRACT Lipid transfer proteins mediate the exchange of lipids between closely apposed membranes at organelle contact sites and play key roles in lipid metabolism, membrane homeostasis, and cellular signaling. A recently discovered novel family of lipid transfer proteins, which includes the VPS13 proteins (VPS13A-D), adopt a rod-like bridge conformation with an extended hydrophobic groove that enables the bulk transfer of membrane lipids for membrane growth. Loss of function mutations in VPS13A and VPS13C cause chorea acanthocytosis and Parkinson’s disease, respectively. VPS13A and VPS13C localize to multiple organelle contact sites, including endoplasmic reticulum (ER) – lipid droplet (LD) contact sites, but the functional roles of these proteins in LD regulation remains mostly unexplored. Here, we employ CRISPR-Cas9 genome editing to generate VPS13A and VPS13C knockout cell lines in U-2 OS cells via deletion of exon 2 and introduction of an early frameshift. Analysis of LD content in these cell lines revealed that loss of either VPS13A or VPS13C results in reduced LD abundance under oleate-stimulated conditions. These data implicate VPS13A and VPS13C in LD regulation and raise the intriguing possibility that VPS13A and VPS13C-mediated lipid transfer facilitates LD biogenesis.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.208
From this paper's citation signal
Citation Network Contribution
0.0771
From 3 citing papers with measurable signal
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 73% comes from its base citations and 27% from the citation network (3 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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