Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila
Ruohong Wang,
Yandong Yin,
Jingshu Li,
Hongmiao Wang,
Wanting Lv,
Yang Gao,
Tangci Wang,
Yedan Zhong,
Zhiwei Zhou,
Yuping Cai,
Xiaoyang Su,
Nan Liu (liunan@sioc.ac.cn) and
Zheng-Jiang Zhu (jiangzhu@sioc.ac.cn)
Additional contact information
Ruohong Wang: Chinese Academy of Sciences
Yandong Yin: Chinese Academy of Sciences
Jingshu Li: Chinese Academy of Sciences
Hongmiao Wang: Chinese Academy of Sciences
Wanting Lv: Chinese Academy of Sciences
Yang Gao: Chinese Academy of Sciences
Tangci Wang: Chinese Academy of Sciences
Yedan Zhong: Chinese Academy of Sciences
Zhiwei Zhou: Chinese Academy of Sciences
Yuping Cai: Chinese Academy of Sciences
Xiaoyang Su: Rutgers University
Nan Liu: Chinese Academy of Sciences
Zheng-Jiang Zhu: Chinese Academy of Sciences
Nature Communications, 2022, vol. 13, issue 1, 1-14
Abstract:
Abstract System-wide metabolic homeostasis is crucial for maintaining physiological functions of living organisms. Stable-isotope tracing metabolomics allows to unravel metabolic activity quantitatively by measuring the isotopically labeled metabolites, but has been largely restricted by coverage. Delineating system-wide metabolic homeostasis at the whole-organism level remains challenging. Here, we develop a global isotope tracing metabolomics technology to measure labeled metabolites with a metabolome-wide coverage. Using Drosophila as an aging model organism, we probe the in vivo tracing kinetics with quantitative information on labeling patterns, extents and rates on a metabolome-wide scale. We curate a system-wide metabolic network to characterize metabolic homeostasis and disclose a system-wide loss of metabolic coordinations that impacts both intra- and inter-tissue metabolic homeostasis significantly during Drosophila aging. Importantly, we reveal an unappreciated metabolic diversion from glycolysis to serine metabolism and purine metabolism as Drosophila aging. The developed technology facilitates a system-level understanding of metabolic regulation in living organisms.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31268-6
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DOI: 10.1038/s41467-022-31268-6
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