Refsofi for Imaging Protein-Protein Interactions in Living Cells in Super-Resolution

Abstract

Virtually all cellular processes depend on networks of highly dynamic protein-protein interactions (PPIs). Hence, deciphering cellular functions at the molecular level requires investigating the spatiotemporal characteristics of PPIs precisely within the context of these signaling networks. However, there is accumulating evidence that protein complexes are often organized into microdomains or nanodomains whose size is below the diffraction limit and thus cannot be sufficiently characterized using standard imaging techniques. Despite the tremendous progress in establishing and refining super-resolution imaging techniques for fluorescently labeled proteins in live cells, observation of protein-protein interactions (PPIs) in super-resolution remains challenging. To address this problem, we developed a strategy in which PPIs induce reconstitution of different fluorescent proteins, whereupon these interactions are resolved in super-resolution using Stochastic Optical Fluctuation Imaging (SOFI) within 30 minutes after complex formation. We employed this reconstituted fluorescence based SOFI (refSOFI) to investigate the interaction between the endoplasmic reticulum Ca2+ sensor STIM1 and the pore forming channel subunit ORAI1, a process crucial for store-operated Ca2+ entry. We found that STIM1-ORAI1 interaction puncta exhibit a smaller size than that suggested by current fluorescence microscopy-based assessments. Moreover, we discovered that the density of these punctate structures is not necessarily dependent on their size. In fact, we observed that STIM1-ORAI1 activation predominantly leads to the formation of new, smaller puncta instead of larger complexes. However, we identified that other perturbing factors can significantly change the size of puncta. These insights critically depend on the obtained super-resolution information. In conclusion, refSOFI represents a versatile tool to examine PPIs in living cells in super-resolution.