Defining Characteristics of a Resilient Organelle Interactome During Aging

About This Grant

Project Summary A growing body of work suggests that aging is not simply the sum of molecular damage, but a systems-level shift in cell physiology—one that compromises resilience, rewires metabolism, and alters the cell’s capacity to adapt to stress. Yet despite deep insight into the aging process from transcriptomic and proteomic profiling, a critical dimension remains obscured: the spatial architecture within the cell. Cellular metabolism is distributed between dynamic, specialized and heterogeneous organelle networks, such that molecular cataloging alone presents an incomplete view of cellular metabolic state and function. Emerging evidence suggests that the way organelles are organized and interconnected defines key aspects of cell identity and performance—and that remodeling of this architecture is a fundamental and underexplored driver of aging. Using the model organism Caenorhabditis elegans, we will apply advanced 3D electron microscopy and artificial intelligence–based image analysis to build the first detailed map of organelle interactions in intact, aging animals. We will also compare age-dependent changes in animals undergoing two mechanistically distinct lifespan-extending interventions, which confer divergent metabolic states. These contrasts collectively will reveal specific features of the organelle ‘interactome’ that are associated with enhanced resilience during aging. Finally, we will develop new genetic tools to visualize and manipulate organelle contact sites in living animals, enabling future studies to test how altering these subcellular interactions affects aging and disease. This research will open a new direction in aging biology by treating intracellular architecture as a regulatory layer that shapes cell fate and function. The data, tools, and frameworks generated will support broad future efforts to understand and target the structural underpinnings of aging across diverse cell types and organisms.