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

Abstract

While single-molecule localization microscopy (SMLM) offers the invaluable prospect to visualize cellular structures below the diffraction limit of light microscopy, its potential could not be 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 analysis of 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. 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 it 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.

Correction of multiple-blinking artefacts in photoactivated localisation microscopy

“…A number of methods have been put forward to test for spatial randomness in SMLM data. These include, for example, methods based on varying the labelling density and observing the effects on specific cluster analysis outputs 28 or by labelling the same species with two different fluorophores allowing a cross-comparison to be made 29 . These methods, however, require multiple sample preparation rounds and are therefore more complex and time-consuming.…”