(721b) Single-Cell Metabolic Objectives during Cell-Type Transitions

Cell-type transitions, crucial for processes including cell quiescence, cell cycle, and embryogenesis, involve intricate metabolic rewiring to optimize competing biological objectives. The competition for cellular resources is often explored through the lens of Pareto optimality and metabolic trade-offs. Despite advancements in understanding these dynamics in unicellular organisms, the metabolic trade-offs in multicellular systems, especially during embryonic cell-state transitions, remain largely unexplored. Addressing this gap, we introduce the Single Cell Optimization Objective and Tradeoff Inference (SCOOTI) framework, a novel computational approach grounded in optimization theory, designed to infer cell-specific metabolic objectives from omics data. By integrating gene expression, protein abundance, and metabolite concentration data with genome-scale metabolic models, SCOOTI leveraged meta-learner regressors to quantitatively elucidate the metabolic objectives underlying cell quiescence, proliferation, and embryogenesis. Our analysis reveals distinct metabolic objectives across cell-cycle phases and embryonic development stages, highlighting the role of specific metabolites in driving these transitions. Notably, the framework uncovers a shift from a high entropy, multitasking metabolic system in early embryogenesis to a more deterministic metabolic focus on biomass production and cell growth in later stages. This shift is exemplified by the trade-offs between glutathione-mediated redox balance and biomass precursor synthesis, suggesting a Pareto optimality scenario where balancing redox status and growth-related objectives is crucial for embryonic development. Our findings challenge the traditional biomass maximization model, proposing instead that cellular metabolic objectives are highly context-dependent, varying significantly between quiescent and proliferative states, and across developmental stages.