Quantitative Super-Resolution Microscopy of Proteins at the Synaptic Level

Single-molecule localization (SML) techniques provide a powerful tool to answer biological questions requiring the observation of subcellular structures at the nanoscale. Quantitative single-molecule analysis allows quantifying the number and distribution of molecules in several biological systems beyond the diffraction limit [1]. In the last few years, many computational methods employing clustering analysis algorithms have been developed to extract quantitative information from SML data sets. In neuroscience, quantitative SML has been applied to reveal density and spatial organization of synaptic proteins [2]. Recently, it has been reported that under plasticity conditions, chemically induced by long term potentiation (iLTP) of inhibitory synapses, GABAA receptors are immobilized and confined at synapses in cultured hippocampal neurons. iLTP expression relies on the recruitment and accumulation of the scaffold protein gephyrin at synaptic areas [3], thereby enhancing the clustering of synaptic GABAA receptors and potentiating GABAergic synaptic currents [4]. In our work we exploit super-resolution approaches (STORM) combined with clustering analysis to study the nanoscale distribution of the inhibitory postsynaptic scaffold, in particular to count GABAA receptors in close proximity to gephyrin nanodomains during iLTP. Furthermore we applied the quantitative SML approaches to study a neuronal protein complex (formed by Protocadherin19, Negr1, FGFR2 and NCAM) involved in neurodevelopmental autism spectrum disorder [5]. We used quantitative STORM to highlight the role of Protocadherin19 in relation to the distribution of the other proteins forming the complex