有机体
代谢组学
多细胞生物
计算生物学
代谢网络
代谢物
模式生物
生物有机体
系统生物学
生物
代谢途径
生物信息学
生化工程
计算机科学
生物信息学
生物系统
细胞
新陈代谢
生物化学
遗传学
生物材料
工程类
基因
作者
Jiyang Dong,Qianwen Peng,Lingli Deng,Jianjun Liu,Huang Wei,Xin Zhou,Changsui Zhao,Zongwei Cai
出处
期刊:iScience
[Cell Press]
日期:2022-09-01
卷期号:25 (9): 104896-104896
被引量:6
标识
DOI:10.1016/j.isci.2022.104896
摘要
The metabolic responses of organism to external stimuli are characterized by the multicellular- and multiorgan-based synergistic regulation. Network analysis is a powerful tool to investigate this multiscale interaction. The imaging mass spectrometry (iMS)-based spatial omics provides multidimensional and multiscale information, thus offering the possibility of network analysis to investigate metabolic response of organism to environmental stimuli. We present iMS dataset-sourced multiscale network (iMS2Net) strategy to uncover prenatal environmental pollutant (PM2.5)-induced metabolic responses in the scales of cell and organ from metabolite abundances and metabolite-metabolite interaction using mouse fetal model, including metabotypic similarity, metabolic vulnerability, metabolic co-variability and metabolic diversity within and between organs. Furthermore, network-based analysis results confirm close associations between lipid metabolites and inflammatory cytokine release. This networking methodology elicits particular advantages for modeling the dynamic and adaptive processes of organism under environmental stresses or pathophysiology and provides molecular mechanism to guide the occurrence and development of systemic diseases.
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