表型
衰老
代谢组学
细胞衰老
仿形(计算机编程)
计算生物学
生物
细胞
生物信息学
细胞生物学
遗传学
计算机科学
基因
操作系统
作者
Ziyi Wang,Si-Yuan Ge,Tiepeng Liao,Man Yuan,Wenwei Qian,Qi Chen,Wei Liang,Xiawei Cheng,Qinghua Zhou,Zhenyu Ju,Hongying Zhu,Wei Xiong
标识
DOI:10.1038/s41467-025-57992-3
摘要
Emerging evidence has unveiled heterogeneity in phenotypic and transcriptional alterations at the single-cell level during oxidative stress and senescence. Despite the pivotal roles of cellular metabolism, a comprehensive elucidation of metabolomic heterogeneity in cells and its connection with cellular oxidative and senescent status remains elusive. By integrating single-cell live imaging with mass spectrometry (SCLIMS), we establish a cross-modality technique capturing both metabolome and oxidative level in individual cells. The SCLIMS demonstrates substantial metabolomic heterogeneity among cells with diverse oxidative levels. Furthermore, the single-cell metabolome predicted heterogeneous states of cells. Remarkably, the pre-existing metabolomic heterogeneity determines the divergent cellular fate upon oxidative insult. Supplementation of key metabolites screened by SCLIMS resulted in a reduction in cellular oxidative levels and an extension of C. elegans lifespan. Altogether, SCLIMS represents a potent tool for integrative metabolomics and phenotypic profiling at the single-cell level, offering innovative approaches to investigate metabolic heterogeneity in cellular processes. Integrated analysis of metabolome and oxidative stress at single-cell level is challenging. Here, the authors develop SCLIMS, enabling simultaneous profiling of metabolome and oxidative stress levels and discoveries of key metabolites regulating oxidative stress, senescence, and healthy aging.
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