Project Summary The retina is often described as a relatively simple part of the central nervous system. Yet, it is composed of approximately 100 distinct cell types and we know very little about what differentiates these cell types from one another at the protein level. The problem with obtaining proteomic data restricted to a particular cell type is that the cell type of interest must be physically dissociated from its surrounding tissue before proteins can be extracted and identified. Attempts to do this invariably lead to cross contamination. A possible solution is offered by in vivo metabolic labeling, or BONCAT. In this approach non-canonical amino acids with azide functional groups are incorporated into protein. The azide then serves as a tag that can be labeled for visualization or affinity purification using click chemistry. In mice, it is possible to restrict the incorporation of the methionine surrogate, azidonorleucine (ANL), to select cell types. This is done through the Cre-dependent expression of a mutant methionyl- acyltransferase (MetRS*) that charges tRNA with ANL instead of methionine. Since only protein synthesized when ANL is present will be labeled, this provides both temporal and spatial control. The goal in this project is to adapt this technology to studies of photoreceptors as a test case for future retinal studies. Mice expressing Cre recombinase in either rods or cones will be crossed with MetRS* mice. We will validate these novel mouse lines, optimize ANL delivery, and test the specificity and sensitivity of click chemistry-mediated proteomic data collection. We expect that adapting this technology to the retina will open the door for both cell-type specific protein profiling and studies of dynamic protein changes in response to disease or various environmental stimulation.