Utilizing the predictable binding kinetics of DNA-PAINT to denoise super-resolution images

TL;DR

This paper introduces a statistical method to reduce noise in DNA-PAINT super-resolution images by removing non-specific binding signals, improving image quality and measurement accuracy.

Contribution

A novel statistical test is introduced to distinguish and remove non-specific binding events in DNA-PAINT imaging.

Findings

The method removes over 90% of non-specific signals in DNA-PAINT super-resolved images.

Denoising enhances the accuracy of spatial relationship and protein quantification measurements.

The technique was validated using Drosophila melanogaster egg chambers.

Abstract

DNA-Point Accumulation for Imaging in Nanoscale Topography (DNA-PAINT) is a versatile super-resolution technique that relies on the predictable binding kinetics between fluorescent imager strands and docking strands attached to target proteins. This makes DNA-PAINT particularly suitable for multiplexing and quantitative applications, but its performance is often limited by spurious signals from non-specific binding of imager strands. Here we describe a method to remove these non-specific binding events using a statistical test to distinguish between DNA-specific and non-specific interactions. To demonstrate the method, we imaged mosaic epithelial tissues in Drosophila melanogaster egg chambers and showed that >90% of non-specific and otherwise indistinguishable signal in the super-resolved images can be removed. This denoising improves the quality of DNA-PAINT super-resolved images and is essential for accurate measurements of spatial relationships and protein quantification.

The performance of DNA-PAINT super-resolution imaging is limited by non-specific binding of the imaging strand. Here, Sirinakis and colleagues report a statistical test that removes these events, improving image quality and measurement accuracy.

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