Proximal interaction networks
Mapping the protein communities that assemble around disease regulators inside living cells.
Proteins rarely act alone. Instead, they work in transient, tightly organized communities that assemble at the right place and moment to drive a cellular decision. The lab maps these communities directly inside living cells using proximity labeling (PL) coupled to quantitative mass spectrometry (qMS). We use APEX2, an engineered proximity-labeling enzyme, fused to a regulator of interest so that it tags neighboring proteins within hundreds of nanometers of the fusion. Cataloging these tagged neighbors by PL-qMS produces a census of the regulator's molecular neighborhood as it exists in the cell.
We use PL-qMS to build topological maps and neighborhoods of proximal networks for master regulators of cellular proliferation, cell death, and differentiation in preclinical models of human prostate cancer. By resolving the neighborhoods separately in different subcellular compartments and across a signaling time course, we will capture how a receptor's protein community reorganizes as the cell commits to one fate over another. The result is a compartment-resolved, time-resolved interaction map that nominates the specific partners through which a signal is transmitted, and that points to the nodes most worth targeting therapeutically in our effort to disrupt cellular signaling underlying different pathological states in human prostate cancers.
