Physical and Genetic Interaction Landscape of the Tyrosine Kinome

Investigator: Nevan Krogan, PhD, MSc
Sponsor: NIH National Institute of General Medical Sciences

Location(s): United States


Tyrosine kinases play a major role in nearly every major disease type and when improperly regulated can cause cancer and diabetes. We will use a highly integrative, systematic approach to map the signaling pathways mediated by tyrosine kinases in mammalian cells. Our findings will illuminate how these proteins drive pathogenesis and guide the rational selection of new drug targets and biomarkers for clinical use.

Signaling by tyrosine kinases play a major role in mammalian signal transduction and is a major component of nearly every major disease type. However, a systematic understanding of signaling pathways has remained elusive. While a number of techniques have been developed to map signaling pathways, used alone they only provide insight into one facet of signaling. We will use an integrative approach to chart the networks which control tyrosine kinase signaling at multiple levels through the use of complementary physical and genetic interaction mapping approaches. These maps will lead to network models which reflect proteins that can functionally modulate signaling and are physically associated with kinases including substrates, adaptors and regulatory subunits. To achieve this, the proposal integrates the complementary expertise of investigators at the University of California-San Francisco in high-throughput physical and genetic interaction mapping (Krogan), chemical-genetic approaches for tracing signaling pathways (Shokat) and network analysis and data integration (Bandyopadhyay). We aim to identify proteins that associate with tyrosine kinases through affinity purification-mass spectrometry (AP-MS) and kinase substrates through covalent capture-and-release in Aim 1. These data will be further characterized using a newly developed platform for quantitative genetic interaction mapping in mammalian cells, which will establish the functional relevance of these interactions by systematically identifying epistatic genetic relationships between kinases and associated proteins in Aim 2. Lastly, in Aim 3, we will unify data collected in the first two aims using network modeling to uncover detailed, mechanistic biological insights relating to mammalian tyrosine kinases. All data (raw, processed and integrated) will be made immediately available in an interactive and searchable fashion so that others can exploit the information we have collected on the tyrosine kinome.