Person:

Asara, John

Characterizing the extent and logic of signaling networks is essential to understanding specificity in such physiological and pathophysiological contexts as cell fate decisions and mechanisms of oncogenesis and resistance to chemotherapy. Cell-based RNA interference (RNAi) screens enable the inference of large numbers of genes that regulate signaling pathways, but these screens cannot provide network structure directly. We describe an integrated network around the canonical receptor tyrosine kinase (RTK)–Ras–extracellular signal–regulated kinase (ERK) signaling pathway, generated by combining parallel genome-wide RNAi screens with protein-protein interaction (PPI) mapping by tandem affinity purification–mass spectrometry. We found that only a small fraction of the total number of PPI or RNAi screen hits was isolated under all conditions tested and that most of these represented the known canonical pathway components, suggesting that much of the core canonical ERK pathway is known. Because most of the newly identified regulators are likely cell type– and RTK-specific, our analysis provides a resource for understanding how output through this clinically relevant pathway is regulated in different contexts. We report in vivo roles for several of the previously unknown regulators, including CG10289 and PpV, the Drosophila orthologs of two components of the serine/threonine–protein phosphatase 6 complex; the Drosophila ortholog of TepIV, a glycophosphatidylinositol-linked protein mutated in human cancers; CG6453, a noncatalytic subunit of glucosidase II; and Rtf1, a histone methyltransferase.

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation and metabolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network surrounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNA interference screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and using quantitative phosphoproteomics, we demonstrate that ~10% of interacting proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes, and validate our method by identifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for study of the evolutionary conserved insulin network.