AbstractsMedical & Health Science

A major challenge of the post-genomics era is to define the connectivity of protein phosphorylation networks. In this thesis, I describe and quantitatively delineate the insulin signalling network in adipocytes by high-resolution mass spectrometry-based proteomics. These data reveal the complexity of intracellular protein phosphorylation. In these studies I identified over 30,000 phosphorylation sites on around 5,000 proteins in this single-cell type, making this amongst the largest phosphoproteomes reported to date. I integrated these large-scale phosphoproteomics data using a machine learning approach to predict physiological substrates of several diverse insulin regulated kinases. This led to the identification of a novel Akt substrate, SIN1, a core component of the mTORC2 complex. I found thatSIN1 is phosphorylated by Akt on threonine 86 (Thr86). I found that phosphorylation of SIN1 Thr86 enhancedmTORC2 activity in response to growth factors, revealing topological insights into the AkUmTOR signalling network. The dynamic phosphoproteome I describe here contains numerous phosphorylation sites on proteins involved in diverse molecular functions and should serve as a useful functional resource for cell biologists.