Quantitative single-molecule mapping of neuronal proteins at the nanoscale

The advent of super-resolution microscopy, also called nanoscopy, allowed a substantial improvement of spatial resolution, opening the door for the observation of biological structures beyond the diffraction limit impossible with conventional light microscopy. Among the super-resolution techniques, single-molecule localization microscopies have proven to be a powerful tool to address many biological issues, since they provide an imaging resolution of the order of tens of nanometers and the possibility to perform quantitative measurements. Neuroscience has been one of the fields in biology to benefit most from super-resolution microscopy. During the last years, single-molecule localization microscopies have been widely exploited to study diffraction-limited subcellular structures in neurons, allowing a deeper understanding of molecular mechanisms underlying neural network functioning and its impairments in pathologies. In this thesis, we developed a tool to investigate the distribution, spatial organization, clustering, and density of neural proteins at the nanoscale. In particular, we focused on the quantitative study of synaptic neurotransmitter receptors and focal adhesions. The knowledge of the distribution and stoichiometry of synaptic proteins is fundamental to understand the regulation of the synaptic transmission in neurons. However, a detailed characterization of the protein architecture within synapses can be achieved only by visualizing them at a nanometric level. Here we propose a quantitative approach based on stochastic optical reconstruction microscopy combined with cluster analysis to investigate the molecular rearrangement of GABAA receptors into subsynaptic domains during synaptic plasticity of the inhibitory neurotransmission. This approach was also applied to the study of the adhesion machinery of mammalian cells and neurons at the interface with single-layer graphene to investigate the interaction between cells and nanostructured materials. Due to their excellent properties and biocompatibility, graphene and its derivatives are the ideal candidates for many biomedical applications, such as neural tissue engineering. However, the adhesion processes at the graphene/neuron interface are still not clear nowadays. Our method offers an easy way to study how graphene substrates can affect adhesion and migration of different types of cells.