Methods for analysis of single molecule localization microscopy to define molecular architecture

A method of defining molecular architecture of a fluorophore labelled structure in a biological sample, the method comprising:

• capturing a series of single molecule localization microscopy (SMLM) optical images of said structure, wherein said structure comprises a protein labelled with a fluorophore;
• mapping a three-dimensional (3D) location of each single emission event in a plurality of single emission events from a series of optical images of a sample to create a 3D point cloud;
• refining the 3D point cloud by merging two or more single emission events into a node within a merge threshold to create a merged 3D point cloud, wherein the merge threshold is based on the resolution limit of the SMLM microscopy;
• completing a multi-threshold network analysis to identify clusters within the refined 3D point cloud;
• and
• extracting features for each cluster at a threshold of 60 nm-140 nm to obtain size, shape and topology of each cluster and thereby define the molecular architecture of the fluorophore labelled structure;
• wherein the extracting features for each cluster uses machine learning.

A method of defining molecular architecture of a fluorophore labelled structure in a biological sample, the method comprising:

• capturing a series of single molecule localization microscopy (SMLM) optical images of said structure, wherein said structure comprises a protein labelled with a fluorophore;
• mapping a three-dimensional (3D) location of each single emission event in a plurality of single emission events from a series of optical images of a sample to create a 3D point cloud;
• refining the 3D point cloud by merging two or more single emission events into a node within a merge threshold to create a merged 3D point cloud, wherein the merge threshold is determined based on an analysis of non-biological networks resulting from multiple emissions from a single fluorophore in the 3D point;
• cloud, wherein multiple emissions from the single fluorophore are two or more emission events within 20 nm;
• completing a multi-threshold network analysis to identify clusters within the refined 3D point cloud;
• and
• extracting features for each cluster at a threshold of 60 nm-140 nm to obtain size, shape and topology of each cluster and thereby define the molecular architecture of the fluorophore labelled structure, wherein the extracting features for each cluster uses machine learning;
• wherein a filtering step removes the non-biological network nano-clusters from the 3D point cloud;
• and
• wherein non-biological networks are distinguished from biological networks in the 3D point cloud by performing a multi-scale network analysis of the 3D point cloud and determining the network degree distribution for each proximity threshold.