We used affinity-purification mass spectrometry to identify 747 candidate proteins that are complexed with Huntingtin (Htt) in distinct brain regions and ages in Huntington's disease (HD) and wild-type mouse brains. To gain a systems-level view of the Htt interactome, we applied Weighted Correlation Network Analysis to the entire proteomic data set to unveil a verifiable rank of Htt-correlated proteins and a network of Htt-interacting protein modules, with each module highlighting distinct aspects of Htt biology. Importantly, the Htt-containing module is highly enriched with proteins involved in 14-3-3 signaling, microtubule-based transport, and proteostasis. Top-ranked proteins in this module were validated as Htt interactors and genetic modifiers in an HD Drosophila model. Our study provides a compendium of spatiotemporal Htt-interacting proteins in the mammalian brain and presents an approach for analyzing proteomic interactome data sets to build in vivo protein networks in complex tissues, such as the brain.
► Proteomic identification of spatiotemporal Huntingtin interactome in the brain ► Analyses of entire proteomic data set using Weighted Gene Correlation Network ► Verifiable Huntingtin-correlated protein ranking and in vivo protein network ► Validation of proteins in Huntingtin network as modifiers of HD fly model
Present address: Department of Neurology, Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham AL 35294, USA
