A cell executes well over 10E8 simultaneous biochemical reactions at hundreds of different locations during every second of its lifetime. Coordinating these innumerable processes is a formidable task that is essential to the correct functioning of each tissue and the entire organism. In response to ever changing internal and external cues, cells have evolved mechanisms that can sense nutrient and energy status and, in response, prompt fine-tuned changes in metabolic activity that buffer these variations. Our recent work has highlighted the role of one organelle, the lysosome, as a gate-keeper of metabolic homeostasis. The lysosome can sense and relay variations in cellular nutrient levels to the master growth regulatory protein kinase mTORC1. In turn, mTORC1 governs catabolic reactions within the lysosome that supply the cell with metabolic building blocks and help maintain global nutrient supply. Importantly, dysregulated lysosomal function is the cause of hereditary metabolic disorders, and is emerging as a contributing factor to the progression of some aggressive cancers. Current technologies that employ mass spectrometers or fluorescent biosensors in whole cells or cell populations cannot reach inside the lysosome to identify and measure the hundreds of metabolites that are generated inside it over time. In order to build a comprehensive, systems-level model of how the lysosome regulates cellular metabolism, a reductionist approach that captures essential spatial and temporal features of lysosomal function in a simplified context is needed. Our goal is to develop a novel in vitro system that wil enable the study of metabolism at the single organelle level. In the current proposal, our system will reconstitute the fusion of lysosomes with organelles known as autophagosomes in test tubes or on the surface of coverslips. Imaging at high spatial and temporal resolution, we will dissect the participation of the lysosome in autophagy, a cellular 'self-eat'process that is essential to the homeostasis of both normal and cancer cells. By scaling up this preparation, and coupling it to high throughput metabolite profiling, we will generate a spatial and temporal 'metabolic map'that profiles hundreds of nutrients generated within the lysosome, describes the time course of their buildup and export, and identifies the transport mechanisms that release these nutrients to the cell. Leveraging the spatial and temporal resolution of our system, we will address a major challenge in present-day cancer research- how highly lethal pancreatic ductal adenocarcinoma (PDAC) exploits autophagy to gain a growth and survival advantage in nutrient-poor microenvironments. Using our 'inside knowledge'of the lysosomal metabolome, we will test the hypothesis that autophagy may allow PDAC cells to maintain homeostasis by tapping into large intracellular reservoirs of nutrients, and we will devise novel strategies to deplete these internal nutrient stores. This project will generate novel tools to illuminate the subcellular organization of metabolism, and lay the foundations for innovative ways to rewire cancer cell metabolism.
A major goal of present-day cancer research, and a potential source of new drug targets, is to identify the mechanisms through which tumor cells rewire their internal metabolism to survive and thrive in challenging, rapidly evolving microenvironments. Achieving this feat requires the ability to study metabolic organization at the subcellular level, which is largely beyond the capabilities of current technologies. The current proposal describes a novel technology that will uncover key mechanisms of metabolic adaptation inside organelles of cancer cells, and will validate these adaptive mechanisms as novel therapeutic targets.
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|Okosun, Jessica; Wolfson, Rachel L; Wang, Jun et al. (2016) Recurrent mTORC1-activating RRAGC mutations in follicular lymphoma. Nat Genet 48:183-8|
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