SuperResNET - single-molecule network analysis detects changes to clathrin structure induced by small-molecule inhibitors.

Abstract

SuperResNET is a network analysis pipeline for the analysis of point cloud data generated by single-molecule localization microscopy (SMLM). Here, we applied SuperResNET network analysis of SMLM direct stochastic optical reconstruction microscopy (dSTORM) data to determine how the clathrin endocytosis inhibitors pitstop 2, dynasore and latrunculin A (LatA) alter the morphology of clathrin-coated pits. SuperResNET analysis of HeLa and Cos7 cells identified three classes of clathrin structures: small oligomers (class I), pits and vesicles (class II), and larger clusters corresponding to fused pits or clathrin plaques (class III). Pitstop 2 and dynasore treatment induced distinct homogeneous populations of class II structures in HeLa cells, suggesting that they arrest endocytosis at different stages. Inhibition of endocytosis was not via actin depolymerization, as the actin-depolymerizing agent LatA induced large, heterogeneous clathrin structures. Ternary analysis of SuperResNET shape features presented a distinct more planar profile for blobs from pitstop 2-treated cells, which aligned with clathrin pits identified with high-resolution minimal photon fluxes (MINFLUX) microscopy, whereas control structures resembled MINFLUX clathrin vesicles. SuperResNET analysis therefore showed that pitstop 2 arrests clathrin pit maturation at early stages of pit formation, representing an approach to detect the effect of small molecules on target structures in situ in the cell from SMLM datasets.