Verifying molecular clusters by 2-color localization microscopy and significance testing

While single-molecule localization microscopy (SMLM) offers the invaluable prospect to visualize cellular structures below the diffraction limit of light microscopy, its potential has not yet been fully capitalized due to its inherent susceptibility to blinking artifacts. Particularly, overcounting of single molecule localizations has impeded a reliable and sensitive detection of biomolecular nanoclusters. Here we introduce a 2-Color Localization microscopy And Significance Testing Approach (2-CLASTA), providing a parameter-free statistical framework for the qualitative analysis of two-dimensional SMLM data via significance testing methods. 2-CLASTA yields p-values for the null hypothesis of random biomolecular distributions, independent of the blinking behavior of the chosen fluorescent labels. The method is parameter-free and does not require any additional measurements nor grouping of localizations. We validated the method both by computer simulations as well as experimentally, using protein concatemers as a mimicry of biomolecular clustering. As the new approach is not affected by overcounting artifacts, it is able to detect biomolecular clustering of various shapes at high sensitivity down to a level of dimers.