Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.

• MeSH
• algoritmy MeSH
• antigeny CD4 genetika   metabolismus   MeSH
• buněčná membrána metabolismus   MeSH
• fluorescenční barviva MeSH
• fluorescenční mikroskopie metody   statistika a číselné údaje   MeSH
• Jurkat buňky MeSH
• lidé MeSH
• membránové proteiny genetika   metabolismus   MeSH
• mutantní proteiny genetika   metabolismus   MeSH
• optické zobrazování metody   statistika a číselné údaje   MeSH
• shluková analýza MeSH
• T-lymfocyty imunologie   metabolismus   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• validační studie MeSH
• Názvy látek
• antigeny CD4 MeSH
• fluorescenční barviva MeSH
• membránové proteiny MeSH
• mutantní proteiny MeSH