The Accuracy of Determining Cluster Size by Analyzing Ripley’s K Function in Single Molecule Localization Microscopy

Ripley’s K function was developed to analyze the spatial distribution characteristics in point pattern analysis, including geography, economics and biomedical research. In biomedical applications, it is popularly used to analyze the clusters of proteins on the cell plasma membrane in single molecule localization microscopy (SMLM), such as photo activated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), universal point accumulation imaging in nanoscale topography (uPAINT), etc. Here, by varying the parameters of the simulated clusters on a modeled SMLM image, the effects of cluster size, cluster separation and protein ratio inside/outside the cluster on the accuracy of cluster analysis by analyzing Ripley’s K function were studied. Although the predicted radius of clusters by analyzing Ripley’s K function did not exactly correspond to the actual radius, we suggest the cluster radius could be estimated within a factor of 1.3. Employing peak analysis methods to analyze the experimental epidermal growth factor receptor (EGFR) clusters at fibroblast-like cell lines derived from monkey kidney tissue - COS7 cell surface observed by uPAINT method, the cluster properties were characterized with errors. Our results present quantification of clusters and can be used to enhance the understanding of clusters in SMLM.

Abstract licence: CC BY

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