Protein aggregation plays a large role in normal cell physiology, but aberrant aggregation also underlies numerous disease pathologies. It is often challenging to study such pathological aggregation, however, because of our inability to visualize protein aggregates in diseased cells. Standard methods for visualization in live cells include either overexpression of a fluorescently tagged construct or direct tagging of the endogenous protein with a fluorescent tag. Not only do these techniques have significant limitations techniques including overexpression artefacts, weak signal, and laborious preparation, but pathological aggregates are often small and thus difficult to visualize through conventional live-cell microscopy. We have recently developed proof-of- principle of a new class or reporter to provide straightforward visualization of endogenous protein aggregates and their dynamics. The goal of this supplement will be to apply this reporter strategy to visualize endogenous pathological aggregates in diseased cells. Specifically, we will target a class of oncogenes called receptor tyrosine kinase fusions, which form protein aggregates within cells. We will design and validate reporter variants that optimally detect and visualize the target aggregates. We will then visualize cluster dynamics across independent cancer cell lines driven by the same receptor fusion. Finally, we will determine the extent to which our reporter can be applied to visualize aggregation dynamics of distinct receptor fusions, of which over 50 have been identified. The described work will validate our new reporter strategy for observation of cellular disease and will have important implications for therapeutic development, for example by allowing visualization of multiple disease states and by establishing a new assay for fluorescence-based drug screens.
This supplement will fund the application of our novel probes of protein aggregation to understand the role of protein clustering in a large class of oncogenes that form aggregates in cells. Success in our aims will provide a roadmap to apply our sensors to visualize and study the aggregation of endogenous proteins across numerous disease states.
