Super-resolution STED imaging in the inner and outer whole-mount mouse retina
Since its invention in 1994, super-resolution microscopy has become a popular tool for advanced imaging of biological structures, allowing visualisation of subcellular structures at a spatial scale below the diffraction limit. Thus, it is not surprising that recently, different super-resolution techniques are being applied in neuroscience, e.g. to resolve the clustering of neurotransmitter receptors and protein complex composition in presynaptic terminals. Still, the vast majority of these experiments were carried out either in cell cultures or very thin tissue sections, while there are only a few examples of super-resolution imaging in thick (> ~50 m) biological samples. In that context, the mammalian whole-mount retina has rarely been studied with super-resolution microscopy. Here, we aimed at establishing a stimulated-emission-depletion (STED) microscopy protocol for imaging whole-mount retina. To this end, we developed sample preparation including horizontal slicing of retinal tissue, an immunolabeling protocol with STED-compatible fluorophores and optimised the STED microscopes settings. We labelled subcellular structures in somata, dendrites, and axons of retinal ganglion cells in the inner mouse retina. Under optimal conditions, we achieved a mean lateral spatial resolution of ~120 nm (using the full width of half-maximum as a proxy) for the thinnest filamentous structures in our preparation and a resolution enhancement of two or higher compared to conventional confocal images. When combined with horizontal slicing of the retina, these settings allowed us visualisation of putative GABAergic horizontal cell synapses in the outer retina with a similar resolution. Taken together, we successfully established a STED protocol for reliable super-resolution imaging in the whole-mount mouse retina, which enables investigating, for instance, protein complex composition and cytoskeletal ultrastructure at retinal synapses in health and disease.