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iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism
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 multidimension...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9418851/ https://www.ncbi.nlm.nih.gov/pubmed/36039290 http://dx.doi.org/10.1016/j.isci.2022.104896 |
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author | Dong, Jiyang Peng, Qianwen Deng, Lingli Liu, Jianjun Huang, Wei Zhou, Xin Zhao, Chao Cai, Zongwei |
author_facet | Dong, Jiyang Peng, Qianwen Deng, Lingli Liu, Jianjun Huang, Wei Zhou, Xin Zhao, Chao Cai, Zongwei |
author_sort | Dong, Jiyang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9418851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94188512022-08-28 iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism Dong, Jiyang Peng, Qianwen Deng, Lingli Liu, Jianjun Huang, Wei Zhou, Xin Zhao, Chao Cai, Zongwei iScience Article 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. Elsevier 2022-08-08 /pmc/articles/PMC9418851/ /pubmed/36039290 http://dx.doi.org/10.1016/j.isci.2022.104896 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Dong, Jiyang Peng, Qianwen Deng, Lingli Liu, Jianjun Huang, Wei Zhou, Xin Zhao, Chao Cai, Zongwei iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title | iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title_full | iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title_fullStr | iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title_full_unstemmed | iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title_short | iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism |
title_sort | ims2net: a multiscale networking methodology to decipher metabolic synergy of organism |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9418851/ https://www.ncbi.nlm.nih.gov/pubmed/36039290 http://dx.doi.org/10.1016/j.isci.2022.104896 |
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