Cluster Recognition by Delaunay Triangulation of Synaptic Proteins in 3D

The advent of super-resolution microscopy opens up the opportunity to study biological structures in unprecedented detail. However, revealing quantitative information about the spatial organization of a set of labeled proteins requires sophisticated analysis. This study introduces a novel robust cluster recognition algorithm based on Delaunay triangulation (CRADT), which can handle complex datasets generated by 3D super-resolution microscopy. This algorithm allows determining volume and shape of protein clusters in 3D. The study demonstrates its performance by applying this algorithm on dual-color 3D super-resolved measurements of mouse hippocampal synapses, stained against the presynaptic active zone marker protein Bassoon and the opposing postsynaptic density protein Homer as well as the exo- and endocytosis machinery proteins Synaptobrevin and Clathrin.