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.
An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates.
一种利用人工智能辅助荧光显微镜系统,通过同时分析线粒体自噬中间体来筛选线粒体自噬诱导剂
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作者:Wang Yicheng, Song Pengfei, Zhou Heqing, Wang Pengwei, Li Yan, Shao Zhiyong, Wang Lu, You Yan, Lei Zuhai, Yu Jinhua, Li Cong
| 期刊: | Nature Communications | 影响因子: | 15.700 |
| 时间: | 2025 | 起止号: | 2025 Jun 4; 16(1):5179 |
| doi: | 10.1038/s41467-025-60315-1 | 研究方向: | 人工智能 |
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