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The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics
BACKGROUND AND PURPOSE: Microbiome dysfunction is known to aggravate acute pancreatitis (AP); however, the relationship between this dysfunction and metabolite alterations is not fully understood. This study explored the crosstalk between the microbiome and metabolites in AP mice. METHODS: Experimen...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10446838/ https://www.ncbi.nlm.nih.gov/pubmed/37621874 http://dx.doi.org/10.3389/fcimb.2023.1134321 |
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author | Zhou, Qi Tao, Xufeng Guo, Fangyue Zhu, Yutong Wu, Yu Xiang, Hong Shang, Dong |
author_facet | Zhou, Qi Tao, Xufeng Guo, Fangyue Zhu, Yutong Wu, Yu Xiang, Hong Shang, Dong |
author_sort | Zhou, Qi |
collection | PubMed |
description | BACKGROUND AND PURPOSE: Microbiome dysfunction is known to aggravate acute pancreatitis (AP); however, the relationship between this dysfunction and metabolite alterations is not fully understood. This study explored the crosstalk between the microbiome and metabolites in AP mice. METHODS: Experimental AP models were established by injecting C57/BL mice with seven doses of cerulein and one dose of lipopolysaccharide (LPS). Metagenomics and untargeted metabolomics were used to identify systemic disturbances in the microbiome and metabolites, respectively, during the progression of AP. RESULTS: The gut microbiome of AP mice primarily included Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria, and “core microbiota” characterized by an increase in Proteobacteria and a decrease in Actinobacteria. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that significantly different microbes were involved in several signaling networks. Untargeted metabolomics identified 872 metabolites, of which lipids and lipid-like molecules were the most impacted. An integrated analysis of metagenomics and metabolomics indicated that acetate kinase (ackA) gene expression was associated with various gut microbiota, including Alistipes, Butyricimonas, and Lactobacillus, and was strongly correlated with the metabolite daphnoretin. The functional gene, O-acetyl-L-serine sulfhydrylase (cysK), was associated with Alistipes, Jeotgalicoccus, and Lactobacillus, and linked to bufalin and phlorobenzophenone metabolite production. CONCLUSION: This study identified the relationship between the gut microbiome and metabolite levels during AP, especially the Lactobacillus-, Alistipes-, and Butyricimonas-associated functional genes, ackA and cysK. Expression of these genes was significantly correlated to the production of the anti-inflammatory and antitumor metabolites daphnoretin and bufalin. |
format | Online Article Text |
id | pubmed-10446838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104468382023-08-24 The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics Zhou, Qi Tao, Xufeng Guo, Fangyue Zhu, Yutong Wu, Yu Xiang, Hong Shang, Dong Front Cell Infect Microbiol Cellular and Infection Microbiology BACKGROUND AND PURPOSE: Microbiome dysfunction is known to aggravate acute pancreatitis (AP); however, the relationship between this dysfunction and metabolite alterations is not fully understood. This study explored the crosstalk between the microbiome and metabolites in AP mice. METHODS: Experimental AP models were established by injecting C57/BL mice with seven doses of cerulein and one dose of lipopolysaccharide (LPS). Metagenomics and untargeted metabolomics were used to identify systemic disturbances in the microbiome and metabolites, respectively, during the progression of AP. RESULTS: The gut microbiome of AP mice primarily included Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria, and “core microbiota” characterized by an increase in Proteobacteria and a decrease in Actinobacteria. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that significantly different microbes were involved in several signaling networks. Untargeted metabolomics identified 872 metabolites, of which lipids and lipid-like molecules were the most impacted. An integrated analysis of metagenomics and metabolomics indicated that acetate kinase (ackA) gene expression was associated with various gut microbiota, including Alistipes, Butyricimonas, and Lactobacillus, and was strongly correlated with the metabolite daphnoretin. The functional gene, O-acetyl-L-serine sulfhydrylase (cysK), was associated with Alistipes, Jeotgalicoccus, and Lactobacillus, and linked to bufalin and phlorobenzophenone metabolite production. CONCLUSION: This study identified the relationship between the gut microbiome and metabolite levels during AP, especially the Lactobacillus-, Alistipes-, and Butyricimonas-associated functional genes, ackA and cysK. Expression of these genes was significantly correlated to the production of the anti-inflammatory and antitumor metabolites daphnoretin and bufalin. Frontiers Media S.A. 2023-08-09 /pmc/articles/PMC10446838/ /pubmed/37621874 http://dx.doi.org/10.3389/fcimb.2023.1134321 Text en Copyright © 2023 Zhou, Tao, Guo, Zhu, Wu, Xiang and Shang 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 | Cellular and Infection Microbiology Zhou, Qi Tao, Xufeng Guo, Fangyue Zhu, Yutong Wu, Yu Xiang, Hong Shang, Dong The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title | The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title_full | The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title_fullStr | The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title_full_unstemmed | The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title_short | The crosstalk between microbiota and metabolites in AP mice: an analysis based on metagenomics and untargeted metabolomics |
title_sort | crosstalk between microbiota and metabolites in ap mice: an analysis based on metagenomics and untargeted metabolomics |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10446838/ https://www.ncbi.nlm.nih.gov/pubmed/37621874 http://dx.doi.org/10.3389/fcimb.2023.1134321 |
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