ArticleScientific reports2021
Single molecule network analysis identifies structural changes to caveolae and scaffolds due to mutation of the caveolin-1 scaffolding domain.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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Who cites it
14 citing papers in PubMed, 23 citations in OpenAlex.
- Caveolae mechanics in cellular functions and disease.Nature reviews. Molecular cell biology · 2026Review
- Membrane remodeling by the collective action of caveolin-1.Nature communications · 2026Article
- Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2026Article
- Phosphorylation-dependent structure and dynamics of caveolin-1 8S complex.Biophysical journal · 2026Article
- ClusterNet: Classifying Single-Molecule Localization Microscopy Datasets with Graph-Based Deep Learning of Supracluster Structure.Small science · 2025Article
- Membrane Remodeling by the Collective Action of Caveolin-1.bioRxiv : the preprint server for biology · 2025Article
- SuperResNET: Model-Free Single-Molecule Network Analysis Software Achieves Molecular Resolution of Nup96.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025Article
- Scaffolds and the scaffolding domain: an alternative paradigm for caveolin-1 signaling.Biochemical Society transactions · 2024Review
- Are There Lipid Membrane-Domain Subtypes in Neurons with Different Roles in Calcium Signaling?Molecules (Basel, Switzerland) · 2023Review
- Physiological functions of caveolae in endothelium.Current opinion in physiology · 2023Article
- A deep learning-based tool for the automated detection and analysis of caveolae in transmission electron microscopy images.Computational and structural biotechnology journal · 2023Article
- SPECHT: Self-tuning Plausibility based object detection Enables quantification of Conflict in Heterogeneous multi-scale microscopy.PloS one · 2022Article
- Studying the Dynamics of Chromatin-Binding Proteins in Mammalian Cells Using Single-Molecule Localization Microscopy.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Caveolin-1 Regulates Cellular Metabolism: A Potential Therapeutic Target in Kidney Disease.Frontiers in pharmacology · 2021Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Caveolin-1 (CAV1), the caveolae coat protein, also associates with non-caveolar scaffold domains. Single molecule localization microscopy (SMLM) network analysis distinguishes caveolae and three scaffold domains, hemispherical S2 scaffolds and smaller S1B and S1A scaffolds. The caveolin scaffolding domain (CSD) is a highly conserved hydrophobic region that mediates interaction of CAV1 with multiple effector molecules. F92A/V94A mutation disrupts CSD function, however the structural impact of CSD mutation on caveolae or scaffolds remains unknown. Here, SMLM network analysis quantitatively shows that expression of the CAV1 CSD F92A/V94A mutant in CRISPR/Cas CAV1 knockout MDA-MB-231 breast cancer cells reduces the size and volume and enhances the elongation of caveolae and scaffold domains, with more pronounced effects on S2 and S1B scaffolds. Convex hull analysis of the outer surface of the CAV1 point clouds confirms the size reduction of CSD mutant CAV1 blobs and shows that CSD mutation reduces volume variation amongst S2 and S1B CAV1 blobs at increasing shrink values, that may reflect retraction of the CAV1 N-terminus towards the membrane, potentially preventing accessibility of the CSD. Detection of point mutation-induced changes to CAV1 domains highlights the utility of SMLM network analysis for mesoscale structural analysis of oligomers in their native environment.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.