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Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats
In recent years, many reports focus on the hepatotoxicity of Gynura segetum root extract (GSrE), but the interaction between GSrE and the gut microbiota is still unclear. This study investigated the mechanism of GSrE-induced hepatotoxicity of different doses and exposure durations by combining metab...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9396145/ https://www.ncbi.nlm.nih.gov/pubmed/36016788 http://dx.doi.org/10.3389/fmicb.2022.947757 |
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author | Gu, Xinyi Li, Shuwei Lu, Mengna Li, Ying Wang, Qixue Chen, Long Jia, Yiqun Cao, Shan Zhang, Ting Zhou, Mingmei Gou, Xiaojun |
author_facet | Gu, Xinyi Li, Shuwei Lu, Mengna Li, Ying Wang, Qixue Chen, Long Jia, Yiqun Cao, Shan Zhang, Ting Zhou, Mingmei Gou, Xiaojun |
author_sort | Gu, Xinyi |
collection | PubMed |
description | In recent years, many reports focus on the hepatotoxicity of Gynura segetum root extract (GSrE), but the interaction between GSrE and the gut microbiota is still unclear. This study investigated the mechanism of GSrE-induced hepatotoxicity of different doses and exposure durations by combining metabolomics and gut microbiota analysis. SD rats were divided into 3 groups: blank, low-dose (7.5 g/kg), and high-dose (15 g/kg) groups. Urine and feces samples were collected on day 0, day 10, and day 21. Metabolomics based on gas chromatography-mass spectrometry (GC-MS) was carried out to identify metabolites and metabolic pathways. 16S rDNA gene sequencing was applied to investigate the composition of gut microbiota before and after GSrE-induced hepatotoxicity. Finally, a correlation analysis of metabolites and gut microbiota was performed. Differential metabolites in urine and feces involved amino acids, carbohydrates, lipids, organic acids, and short chain fatty acids. Among them, L-valine, L-proline, DL-arabinose, pentanoic acid, D-allose, and D-glucose in urine and D-lactic acid and glycerol in fecal metabolites depended on the exposure of time and dose. In addition, 16S rDNA sequencing analysis revealed that GSrE-induced hepatotoxicity significantly altered the composition of gut microbiota, namely, f_Muribaculaceae_Unclassified, Lactobacillus, Bacteroides, Lachnospiraceae_NK4A136_group, f_Ruminococcaceae_Unclassified, Prevotellaceae_Ga6A1_group, and Escherichia-Shigella. The correlation analysis between gut microbiota and differential metabolites showed the crosstalk between the gut microbiota and metabolism in host involving energy, lipid, and amino acid metabolisms. In summary, our findings revealed that peripheral metabolism and gut microbiota disorders were time- and dose-related and the correlation between gut microbiota and metabolites in GSrE-induced hepatotoxicity. |
format | Online Article Text |
id | pubmed-9396145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93961452022-08-24 Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats Gu, Xinyi Li, Shuwei Lu, Mengna Li, Ying Wang, Qixue Chen, Long Jia, Yiqun Cao, Shan Zhang, Ting Zhou, Mingmei Gou, Xiaojun Front Microbiol Microbiology In recent years, many reports focus on the hepatotoxicity of Gynura segetum root extract (GSrE), but the interaction between GSrE and the gut microbiota is still unclear. This study investigated the mechanism of GSrE-induced hepatotoxicity of different doses and exposure durations by combining metabolomics and gut microbiota analysis. SD rats were divided into 3 groups: blank, low-dose (7.5 g/kg), and high-dose (15 g/kg) groups. Urine and feces samples were collected on day 0, day 10, and day 21. Metabolomics based on gas chromatography-mass spectrometry (GC-MS) was carried out to identify metabolites and metabolic pathways. 16S rDNA gene sequencing was applied to investigate the composition of gut microbiota before and after GSrE-induced hepatotoxicity. Finally, a correlation analysis of metabolites and gut microbiota was performed. Differential metabolites in urine and feces involved amino acids, carbohydrates, lipids, organic acids, and short chain fatty acids. Among them, L-valine, L-proline, DL-arabinose, pentanoic acid, D-allose, and D-glucose in urine and D-lactic acid and glycerol in fecal metabolites depended on the exposure of time and dose. In addition, 16S rDNA sequencing analysis revealed that GSrE-induced hepatotoxicity significantly altered the composition of gut microbiota, namely, f_Muribaculaceae_Unclassified, Lactobacillus, Bacteroides, Lachnospiraceae_NK4A136_group, f_Ruminococcaceae_Unclassified, Prevotellaceae_Ga6A1_group, and Escherichia-Shigella. The correlation analysis between gut microbiota and differential metabolites showed the crosstalk between the gut microbiota and metabolism in host involving energy, lipid, and amino acid metabolisms. In summary, our findings revealed that peripheral metabolism and gut microbiota disorders were time- and dose-related and the correlation between gut microbiota and metabolites in GSrE-induced hepatotoxicity. Frontiers Media S.A. 2022-08-09 /pmc/articles/PMC9396145/ /pubmed/36016788 http://dx.doi.org/10.3389/fmicb.2022.947757 Text en Copyright © 2022 Gu, Li, Lu, Li, Wang, Chen, Jia, Cao, Zhang, Zhou and Gou. 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 | Microbiology Gu, Xinyi Li, Shuwei Lu, Mengna Li, Ying Wang, Qixue Chen, Long Jia, Yiqun Cao, Shan Zhang, Ting Zhou, Mingmei Gou, Xiaojun Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title | Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title_full | Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title_fullStr | Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title_full_unstemmed | Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title_short | Investigation of Gynura segetum root extract (GSrE) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
title_sort | investigation of gynura segetum root extract (gsre) induced hepatotoxicity based on metabolomic signatures and microbial community profiling in rats |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9396145/ https://www.ncbi.nlm.nih.gov/pubmed/36016788 http://dx.doi.org/10.3389/fmicb.2022.947757 |
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