Visual Proteomics for studying subcellular protein dynamics

Advances in mass-spectrometry based proteomics have yielded deep insights into the protein-protein interaction networks in intact cells. However, assessing dynamic changes across the entire proteome is still challenging, and some processes like localization changes on the subcellular and sub-organelle level are not easily detected. We recently developed an alternative mass-spectrometry independent approach, using pooled intron tagging and fluorescence microscopy to visualize the localizations and levels of hundreds of metabolic enzymes in parallel. Here, we aim to expand this technology to proteome-wide scale, and validate it extensively. We further apply it to test the hypothesis that subcellular and sub- organellar localization of proteins impacts their dynamic behavior following perturbation of protein homeostasis, with a particular focus on drugs and targets associated with multiple myeloma. We will generate a cell pool reporting on more than 5,000 proteins expressed from their endogenous promoters. In parallel, we will develop the computational framework for automatic recognition of these clones based on the clone-specific levels and localizations of proteins tagged in five complementary fluorescent channels. We will then expose the cell pool to chemical perturbations that are known to exert global dynamic changes on the localization and abundance of multiple proteins. The expected changes to selected proteins in these conditions will allow us to both functionally validate our cell pool and benchmark our analysis pipeline. We expect that in addition to rediscovering known alterations, we will also observe changes in the localizations and levels of additional proteins. For these proteins, we will then validate the observed localization changes and their functional relevance on endogenous untagged proteins. This project aims at establishing a highly innovative novel technology for the detection of changes to the proteome based on imaging of tagged cell pools. In contrast to alternative technologies, this approach is readily transferable to different cell models and enables the detection of changes not only in the abundance but also in the subcellular localizations of proteins. The latter is of particular importance to test whether proteins in different (sub)organellar localizations respond differently to perturbation of protein homeostasis.