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Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks

AIM: Chinese medicine Danhong injection (DHI) is an effective pharmaceutical preparation for treating cerebral infarction. Our previous study shows that DHI can remarkably reduce the ischemic stroke-induced infarct volume in a dose-dependent manner, but the pharmacological mechanism of the DHI dose-...

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Autores principales: Qi, Yifei, Zhou, Niwen, Jiang, Qing, Wang, Zhi, Zhang, Yingying, Li, Bing, Xu, Wenjuan, Liu, Jun, Wang, Zhong, Zhu, Lixing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439200/
https://www.ncbi.nlm.nih.gov/pubmed/34531713
http://dx.doi.org/10.3389/fnins.2021.645185
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author Qi, Yifei
Zhou, Niwen
Jiang, Qing
Wang, Zhi
Zhang, Yingying
Li, Bing
Xu, Wenjuan
Liu, Jun
Wang, Zhong
Zhu, Lixing
author_facet Qi, Yifei
Zhou, Niwen
Jiang, Qing
Wang, Zhi
Zhang, Yingying
Li, Bing
Xu, Wenjuan
Liu, Jun
Wang, Zhong
Zhu, Lixing
author_sort Qi, Yifei
collection PubMed
description AIM: Chinese medicine Danhong injection (DHI) is an effective pharmaceutical preparation for treating cerebral infarction. Our previous study shows that DHI can remarkably reduce the ischemic stroke-induced infarct volume in a dose-dependent manner, but the pharmacological mechanism of the DHI dose-dependent relationship is not clear. Therefore, the dose-dependent efficacy of DHI on cerebral ischemia and the underlying mechanisms were further investigated in this study. METHODS: A middle cerebral artery occlusion (MCAO) model was established and the rats were randomly divided into six groups: sham, vehicle, DHI dose-1, DHI dose-2, DHI dose-3, and DHI dose-4. Forty-one metabolites in serum were selected as candidate biomarkers of efficacy phenotypes by the Agilent 1290 rapid-resolution liquid chromatography system coupled with the Agilent 6550 Q-TOF MS system. Then, the metabolic networks in each group were constructed using the Weighted Correlation Network analysis (WGCNA). Moreover, the Yang and Yin transformation of six patterns (which are defined by up- and downregulation of metabolites) and synchronous modules divided from a synchronous network were used to dynamically analyze the mechanism of the drug’s effectiveness. RESULTS: The neuroprotective effect of DHI has shown a dose-dependent manner, and the high-dose group (DH3 and DH4) effect is better. The entropy of the metabolic network and the Yin/Yang index both showed a consistent dose–response relationship. Seven dose-sensitive metabolites maintained constant inverse upregulation or downregulation in the four dose groups. Three synchronous modules for the DH1–DH4 full-course network were identified. Glycine, N-acetyl-L-glutamate, and tetrahydrofolate as a new emerging module appeared in DH2/DH3 and enriched in glutamine and glutamate metabolism-related pathways. CONCLUSION: This study takes the DHI metabolic network as an example to provide a new method for the discovery of multiple targets related to pharmacological effects. Our results show that the three conservative allosteric module nodes, taurine, L-tyrosine, and L-leucine, may be one of the basic mechanisms of DHI in the treatment of cerebral infarction, and the other three new emerging module nodes glyoxylate, L-glutamate, and L-valine may participate in the glutamine and glutamate metabolism pathway to improve the efficacy of DHI.
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spelling pubmed-84392002021-09-15 Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks Qi, Yifei Zhou, Niwen Jiang, Qing Wang, Zhi Zhang, Yingying Li, Bing Xu, Wenjuan Liu, Jun Wang, Zhong Zhu, Lixing Front Neurosci Neuroscience AIM: Chinese medicine Danhong injection (DHI) is an effective pharmaceutical preparation for treating cerebral infarction. Our previous study shows that DHI can remarkably reduce the ischemic stroke-induced infarct volume in a dose-dependent manner, but the pharmacological mechanism of the DHI dose-dependent relationship is not clear. Therefore, the dose-dependent efficacy of DHI on cerebral ischemia and the underlying mechanisms were further investigated in this study. METHODS: A middle cerebral artery occlusion (MCAO) model was established and the rats were randomly divided into six groups: sham, vehicle, DHI dose-1, DHI dose-2, DHI dose-3, and DHI dose-4. Forty-one metabolites in serum were selected as candidate biomarkers of efficacy phenotypes by the Agilent 1290 rapid-resolution liquid chromatography system coupled with the Agilent 6550 Q-TOF MS system. Then, the metabolic networks in each group were constructed using the Weighted Correlation Network analysis (WGCNA). Moreover, the Yang and Yin transformation of six patterns (which are defined by up- and downregulation of metabolites) and synchronous modules divided from a synchronous network were used to dynamically analyze the mechanism of the drug’s effectiveness. RESULTS: The neuroprotective effect of DHI has shown a dose-dependent manner, and the high-dose group (DH3 and DH4) effect is better. The entropy of the metabolic network and the Yin/Yang index both showed a consistent dose–response relationship. Seven dose-sensitive metabolites maintained constant inverse upregulation or downregulation in the four dose groups. Three synchronous modules for the DH1–DH4 full-course network were identified. Glycine, N-acetyl-L-glutamate, and tetrahydrofolate as a new emerging module appeared in DH2/DH3 and enriched in glutamine and glutamate metabolism-related pathways. CONCLUSION: This study takes the DHI metabolic network as an example to provide a new method for the discovery of multiple targets related to pharmacological effects. Our results show that the three conservative allosteric module nodes, taurine, L-tyrosine, and L-leucine, may be one of the basic mechanisms of DHI in the treatment of cerebral infarction, and the other three new emerging module nodes glyoxylate, L-glutamate, and L-valine may participate in the glutamine and glutamate metabolism pathway to improve the efficacy of DHI. Frontiers Media S.A. 2021-08-20 /pmc/articles/PMC8439200/ /pubmed/34531713 http://dx.doi.org/10.3389/fnins.2021.645185 Text en Copyright © 2021 Qi, Zhou, Jiang, Wang, Zhang, Li, Xu, Liu, Wang and Zhu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Qi, Yifei
Zhou, Niwen
Jiang, Qing
Wang, Zhi
Zhang, Yingying
Li, Bing
Xu, Wenjuan
Liu, Jun
Wang, Zhong
Zhu, Lixing
Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title_full Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title_fullStr Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title_full_unstemmed Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title_short Dose-Dependent Variation of Synchronous Metabolites and Modules in a Yin/Yang Transformation Model of Appointed Ischemia Metabolic Networks
title_sort dose-dependent variation of synchronous metabolites and modules in a yin/yang transformation model of appointed ischemia metabolic networks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439200/
https://www.ncbi.nlm.nih.gov/pubmed/34531713
http://dx.doi.org/10.3389/fnins.2021.645185
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