The CASTOR Proteins Are Arginine Sensors for the mTORC1 Pathway

Amino acids signal to the mTOR complex I (mTORC1) growth pathway through the Rag GTPases. Multiple distinct complexes regulate the Rags, including GATOR1, a GTPase activating protein (GAP), and GATOR2, a positive regulator of unknown molecular function. Arginine stimulation of cells activates mTORC1, but how it is sensed is not well understood. Recently, SLC38A9 was identified as a putative lysosomal arginine sensor required for arginine to activate mTORC1 but how arginine deprivation represses mTORC1 is unknown. Here, we show that CASTOR1, a previously uncharacterized protein, interacts with GATOR2 and is required for arginine deprivation to inhibit mTORC1. CASTOR1 homodimerizes and can also heterodimerize with the related protein, CASTOR2. Arginine disrupts the CASTOR1-GATOR2 complex by binding to CASTOR1 with a dissociation constant of ∼30 μM, and its arginine-binding capacity is required for arginine to activate mTORC1 in cells. Collectively, these results establish CASTOR1 as an arginine sensor for the mTORC1 pathway.United States. National Institutes of Health (R01CA103866)United States. National Institutes of Health (AI47389)United States. Department of Energy (W81XWH-07-0448)United States. National Institutes of Health (F31 CA180271)United States. National Institutes of Health (F31 CA189437

Architecture of the human interactome defines protein communities and disease networks

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease1–3. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL)5 of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization

The BioPlex Network: A Systematic Exploration of the Human Interactome

SummaryProtein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%–100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors