Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

Hesam Mazidi, Tianben Ding, Arye Nehorai and Matthew D. Lew ()
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Hesam Mazidi: Washington University in St. Louis
Tianben Ding: Washington University in St. Louis
Arye Nehorai: Washington University in St. Louis
Matthew D. Lew: Washington University in St. Louis

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract The resolution and accuracy of single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration rulers, or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of reconstructed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

Date: 2020
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DOI: 10.1038/s41467-020-20056-9

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