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Description
Single Molecule Localization Microscopy (SMLM) surpasses diffraction limit by separating signal from individual proteins in time. Although the usual resolution limit is around 20 nm for most techniques, DNA-PAINT [1] and RESI [2] achieve the resolution at the level of individual proteins. Inferring protein positions from sets of localizations is key to examining oligomeric configurations of biomolecules. To do so, a clustering algorithm, here referred to as “Radial Clusterer” (RC), has been applied in DNA-PAINT [3] and RESI [2]. However, this algorithm is suboptimal as it requires the proteins imaged in the same round to be spaced by around 4 times the localization precision (), well above the standard resolution limit of 2.35.
Here we present the application of Gaussian Mixture Modeling (GMM) [4] to localization clouds to pinpoint protein positions by maximum likelihood estimation in 2D and 3D data (astigmatism). GMM utilizes the unique nature of fluorophore “blinking” in DNA-PAINT, i.e., its independence (no fluorophore-fluorophore interaction) and repetitiveness (stability over long image acquisition), which result in numerous localizations that are normally distributed around the imaged targets.
GMM is capable of resolving targets spaced by 2.35, without any need for additional hardware adaptation and in a computationally efficient fashion. GMM shows superior performance compared to RC in DNA origami and cellular data. By applying GMM to standard DNA-PAINT image of Nup96, combined with an averaging model [5], we were able to reconstruct the 16 copies of the protein in the cytoplasmic ring and retrieve the cryoEM-based molecular distances [6], so far achieved in light microscopy only by RESI. By extracting more information, GMM will boost the performance of DNA-PAINT and RESI, especially for dense targets. To maximize its impact, GMM has been implemented as a Picasso [1] plugin.
[1] – Schnitzbauer, et al. Nature Prot. 2017
[2] – Reinhardt, et al. Nature. 2023
[3] – Schlichthaerle, et al. Nature Comm. 2021
[4] – Dempster, et al. JRSS. 1977
[5] – Wu, et al. Nature Met. 2023
[6] – Schuller, et al. Nature. 2021
| Authors | Rafal Kowalewski*, Susanne C. M. Reinhardt, Luciano A. Masullo, Shuhan Xu, Eduard Unterauer and Ralf Jungmann |
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| Keywords | Single Molecule Localization Microscopy, DNA-PAINT, Data Analysis, Molecular Patterns |
