Mapping Functional Protein Neighborhoods in the Mouse Brain

Abstract

New proteomics methods make it possible to determine protein interaction maps at the proteome scale without the need for genetically encoded tags, opening up new organisms and tissue types to investigation. Current molecular and computational methods are oriented towards protein complexes that are soluble, stable, and discrete. However, the mammalian brain, among the most complicated and most heavily studied tissue types, derives many of its unique functions from protein interactions that are neither discrete nor soluble. Proteomics investigations into the global protein interaction landscape of the brain have therefore leveraged non-proteomics datasets to supplement their experiments. Here, we develop a novel, integrative proteomics pipeline and apply it to infer a global map of functional protein neighborhoods in the mouse brain without the aid of external datasets. By leveraging synaptosome enrichment and interactomics methods that target both soluble and insoluble protein fractions, we resolved protein interactions for key neural pathways, including those from refractory subcellular fractions such as the membrane and cytoskeleton. In comparison to external datasets, our observed interactions perform similarly to hand-curated synaptic protein interactions while also suggesting thousands of novel connections. We additionally employed cleavable chemical cross-linkers to detect direct binding partners and provide structural context. Our combined map suggests new protein pathways and novel mechanisms for proteins that underlie neurological diseases, including autism and epilepsy. Our results show that proteomics methods alone are sufficient to determine global interaction maps for proteins that are of broad interest to neuroscience. We anticipate that our map will be used to prioritize new research avenues and will pave the way towards future proteomics techniques that resolve protein interactions at ever greater resolution.