Deciphering synaptic receptor distributions, clustering and stoichiometry using spatial intensity distribution analysis (SpIDA)

Measuring protein interactions in subcellular compartments is key to understanding cell signalling mechanisms, but quantitative analysis of these interactions in situ has remained a major challenge. This thesis presents a novel analysis technique, spatial intensity distribution analysis (SpIDA), which may be applied to images obtained using fluorescence microscopy. SpIDA measures fluorescent particle densities and oligomerization states within individual images. The method is based on fitting intensity histograms from single images with super-Poissonian distributions to obtain density maps of fluorescent molecules and their quantal brightness. Since distributions are acquired spatially rather than temporally, this analysis may be applied to both live and chemically fixed cells and tissue. The technique does not rely on spatial correlations, freeing it from biases due to subcellular compartmentalization and heterogeneity within tissue samples. First, we validated the analysis technique evaluating its limits and demonstrating how it can be used to obtain useful information from complex biological samples. Analysis of simulations and heterodimeric GABAB receptors in spinal cord samples shows that the approach yields accurate estimates over a broad range of densities. SpIDA is applicable to sampling within subcell areas and reveals the presence of monomers and multimers with single dye labeling. We show that the substance P receptor (NK-1r) almost exclusively forms homodimers on the membrane and is primarily monomeric in the cytoplasm of dorsal horn neurons. Triggering receptor internalization caused a measurable decrease in homodimer density on the membrane surface. Finally, using GFP-tagged receptor subunits, we show that SpIDA can resolve dynamic changes in receptor oligomerization in live cells and is applicable to detection of high order oligomerization states. We then compared SpIDA results with those obtained from fluorescence lifetime imaging, and used it to extract information on receptor tyrosine kinase (RTK) dimerization at the cell membrane in response to GPCR activation. We show that RTK dimerization can be used as an index of activation or transactivation and then characterize the level of transactivation of many RTK-GPCR pairs, with cell cultures and primary neuron cultures with endogenous levels of RTKs and GPCRs. Dose-response curves were obtained from which pharmalogical parameters can be compared for each GPCR studied. Our data demonstrates that by allowing for time and space quantification of heterogenous oligomeric states, SpIDA enables systematic quantitative mechanistic studies not only of RTK transactivation at the cell membrane, but also of other cell signaling processes involving changes in protein oligomerization, trafficking and activity in different subcellular localizations. Finally, we studied the changes in number of synaptic sites in the neurons of the dorsal horn of the spinal cord of rats after a peripheral nerve injury (PNI), which consists of our model for chronic pain. We show that, after the PNI, there is a general decrease in synaptic sites together with a scaling or increasing of some of the GABAA receptor subunits. This scaling of the GABAA receptors at the postsynaptic sites was replicated by incubating the histological sections in a brain derivative nerve factor. Furthermore, we use SpIDA to obtain stoichiometry information for the GABAA receptor subunits directly at the postsynaptic sites. In short, we observe a switch from receptors containing two alpha1 to receptors containing two alpha2 and alpha3. This general change in subunits will have a direct effect on the cell as it will have different effects on the cell membrane conductance in response to GABA. As demonstrated, the advantages and greater versatility of SpIDA over current techniques opens the door to a new level of quantification for studies of protein interactions in native tissue using standard fluorescence microscopy.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.