粒体自噬
荧光
诱导剂
化学
计算生物学
生物物理学
细胞生物学
纳米技术
生物化学
生物
物理
材料科学
量子力学
自噬
基因
细胞凋亡
作者
Yicheng Wang,Pengfei Song,Heqing Zhou,Pengwei Wang,Yan Li,Zhiyong Shao,Lu Wang,Yan You,Zuhai Lei,Jinhua Yu,Cong Li
标识
DOI:10.1038/s41467-025-60315-1
摘要
Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment of mitophagy flux, a process involving multiple sequential intermediates, is implicated in the onset of numerous neurodegenerative diseases. Screening mitophagy inducers, particularly understanding their impact on mitophagic intermediates, is crucial for neurodegenerative disease treatment. However, existing techniques do not allow simultaneous visualization of distinct mitophagic intermediates in live cells. Here, we introduce an artificial intelligence-assisted fluorescence microscopic system (AI-FM) that enables the uninterrupted recognition and quantification of key mitophagic intermediates by extracting mitochondrial pH and morphological features. Using AI-FM, we identify a potential mitophagy modulator, Y040-7904, which enhances mitophagy by promoting mitochondria transport to autophagosomes and the fusion of autophagosomes with autolysosomes. Y040-7904 also reduces amyloid-β pathologies in both in vitro and in vivo models of Alzheimer's disease. This work offers an approach for visualizing the entire mitophagy flux, advancing the understanding of mitophagy-related mechanisms and enabling the discovery of mitophagy inducers for neurodegenerative diseases.
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