Single-Molecule Clustering for Super-Resolution Optical Fluorescence Microscopy

Molecular assembly in a complex cellular environment is vital for understanding underlying biological mechanisms. Biophysical parameters (such as single-molecule cluster density, cluster-area, pairwise distance, and number of molecules per cluster) related to molecular clusters directly associate with the physiological state (healthy/diseased) cell. Using super-resolution imaging along powerful clustering methods (K-means, Gaussian mixture, point clustering), we estimated these critical biophysical associated dense sparse clusters. We investigated Hemaglutinin (HA) an Influenza type A disease model. Subsequently, were transfected NIH3T3 cells. Investigations on test sample (randomly generated clusters) cells (expressing Dendra2-Hemaglutinin (Dendra2-HA) photoactivable molecules) show significant disparity among existing techniques. It observed that single method inadequate estimating all relevant accurately. Thus, multimodel approach necessary order characterize determine parameters. The proposed study involving optical system development, synthesis, advanced may facilitate better Potential applications are emerging field cell biology, biophysics, fluorescence imaging.