ERC Starting Grants: Evolution of Biomolecular Condensates: CONDEVO

Programme(s): HORIZON.1.1 - European Research Council (ERC) 

Topic(s): ERC-2023-STG - ERC STARTING GRANTS

Call for proposal: ERC-2023-STG

Funding Scheme: HORIZON-ERC - HORIZON ERC Grants

Grant agreement ID: 101116284

Objective: Cells organize billions of protein molecules into membrane-bound and membraneless compartments, called biomolecular condensates. Previous research on condensates focused on identifying their components, material properties, and function in homeostasis and disease. In contrast to our relatively precise understanding of membrane-bound compartments, we lack a comprehensive picture of the mechanisms that target proteins into condensates and how condensates emerged during evolution. I hypothesize that localization into condensate is encoded in protein sequences, and that functional condensates are under selection pressure and therefore conserved. I propose a comprehensive research program including both theoretical and experimental approaches to reveal how and when protein condensates emerged during evolution. I propose to: 1. Map proteomes of condensates across the tree of life, 2. Reconstruct the history of condensates, 3. Follow trajectories of condensate evolution. Specifically, I will: 1. Investigate what conserved sequence features drive localization to condensates by developing computational tools to predict the proteome of specific condensates across the tree of life; and by testing partitioning of proteins into condensates experimentally. 2. Reconstruct the evolutionary history of the protein components of conserved condensates, and thereby trace their evolutionary origin. Analogous to protein families, we will define condensate families based on shared properties of their proteins and function by developing similarity metrics. We will reconstruct the phylogeny of condensate families and compare to organism and organelle evolution. 3. Perform directed evolution of ancestral non-condensate-forming proteins towards condensate partitioning and follow their mutational trajectories. Building on our already developed tools and the new algorithms proposed here combined with experiments, we will be able to map the molecular history of condensates on the Tree of Life.