iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism

Jiyang Dong, Qianwen Peng, Lingli Deng, Jianjun Liu, Wei Huang, Xin Zhou, Chao Zhao*, Zongwei Cai*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number104896
JournaliScience
Volume25
Issue number9
Early online date8 Aug 2022
DOIs
Publication statusPublished - 16 Sept 2022

Scopus Subject Areas

  • General

User-Defined Keywords

  • Metabolomics
  • Omics
  • Systems biology

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