To Örebro University

Localization microscopy methods like Stochastic Optical Reconstruction Microscopy (STORM) are very well suited for exploring clustering of proteins, as the data inherently provide a list of molecular coordinates. Here we use state-of-art cluster analysis algorithms (DBSCAN) to explore the clustering behaviour of different affinity forms of the integrin LFA-1. It has been suggested that LFA-1 may form clusters, in order to increase the avidity to ICAM-1. However, this hypothesis still seems to be controversial. In this study, we found, variations in clustering behaviour among the different affinity forms of LFA-1 in migrating T-cells. We found that panLFA-1 is located in clusters throughout the polarized cell on ICAM-1, with an increased density of molecules and clusters in the mid area and rear of the cell, whereas the intermediate and high affinity form of LFA-1 showed an increased number in the mid area of a migrating cell and the high affinity form of LFA-1 in the front and rear. Together, these data suggest that, in addition to LFA-1 conformation, protein clustering might play a role in controlling cell-substrate adhesion on ICAM-1. By applying the cluster analysis algorithm DBSCAN to localization microscopy data, integrin clusters could be identified and different cluster parameters could be quantified.