Prompt Description

APPROVED This is the abstract of my project proposal. Please generate a scheme for it. Abstract: Asymmetric segregation of protein damage and "aged proteins" during cell division is considered a key mechanism in the initiation of aging and cellular rejuvenation. However, existing studies mainly rely on observing a few fluorescently labeled molecules, lacking the ability to globally analyze at the molecular level and making it difficult to distinguish between new, old, and damaged proteins. To address these issues, this project proposes to use human cells as a model, combining live-cell fluorescence imaging, metabolic isotope labeling, and single-cell proteomics to systematically study the differential segregation patterns of protein abundance, new/old ratios, and damaged components between sister daughter cells during cell division. By constructing a SNAP-Omp25 mitochondrial temporal labeling system, we aim to capture asymmetric segregation events and perform Astral DIA single-cell proteomic analysis on strictly paired sister daughter cells to obtain high-resolution molecular readouts. Furthermore, we will introduce machine learning methods to extract stable asymmetrically segregated proteins and functional modules, and verify their regulatory roles through genetic and pharmacological interventions. This study will elucidate the molecular mechanisms of protein homeostasis resetting and damage isolation in human cells, laying the foundation for understanding aging mechanisms and intervention strategies for related diseases.