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对圈养环境中肠道微生物群和代谢产物对阿苯达唑驱虫反应的多组学见解

Multi-omics insights into the response of the gut microbiota and metabolites to albendazole deworming in captive .

作者信息

Qin Xinxi, Han Jincheng, Xi Li, Zhao Longfei, Li Zhiqiang, Cui Yanyan, Hao Junfang

机构信息

College of Biology and Food, Shangqiu Normal University, Shangqiu, China.

College of Veterinary Medicine, Northwest A&F University, Xianyang, China.

出版信息

Front Microbiol. 2025 Apr 23;16:1581483. doi: 10.3389/fmicb.2025.1581483. eCollection 2025.

DOI:10.3389/fmicb.2025.1581483
PMID:40336838
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12058082/
Abstract

BACKGROUND

Parasite infection and deworming treatment affect the host gut microbiota. Exploring the response mechanism of the gut microbiota in () to albendazole deworming treatment is of great value for protecting this critically endangered species.

METHODS AND RESULTS

This study used metataxonomics and metabolomics to explore the responses of the gut microbiota and metabolites of to albendazole deworming treatment. The results showed that deworming significantly reduced the eggs per gram of feces (EPG). The 16S rRNA gene sequencing results showed that the richness and diversity of the gut microbiota in after deworming were significantly increased. Meanwhile, deworming treatment also changed the composition of the gut microbiota. At the genus level, the , , , , and were significantly enriched in the pre-deworming samples. , , and were significantly enriched in the post-deworming samples. Metabolomics analysis revealed that the relative abundance of 382 out of 1,865 metabolites showed significant differences between the pre- and post-deworming samples. Among them, 103 metabolites were annotated based on the HMDB and mainly classified into Prenol lipids, Carboxylic acids and derivatives, and Organooxygen compounds, etc. The KEGG enrichment analysis result indicated that these metabolites were mainly involved in energy, amino acid, lipid, and purine metabolism. Correlation analysis showed that and , whose relative abundances were upregulated after deworming treatment, were positively correlated with Kaempferol, 5,7-Dihydroxy-3-methoxy-4'-prenyloxyflavone, Purpurin, and Rhein, which have anti-parasitic activities. The , with a downregulated relative abundance after deworming treatment, was not only negatively correlated with the above four metabolites, but also positively correlated with Retinyl beta-glucuronide, which is a storage form of vitamin A, and positively correlated with CDP-Choline, which increases the host's susceptibility to and .

CONCLUSION

This study emphasizes that deworming treatment has an impact on the gut microbiota and metabolic functions of . By exploiting the correlations between differential microbiota and metabolites, potential probiotics or prebiotics can be explored, thereby enhancing the efficiency of deworming and reducing its side effects.

摘要

背景

寄生虫感染和驱虫治疗会影响宿主肠道微生物群。探索(某物种)肠道微生物群对阿苯达唑驱虫治疗的反应机制,对于保护这种极度濒危物种具有重要价值。

方法与结果

本研究采用宏分类学和代谢组学方法,探索(某物种)肠道微生物群和代谢产物对阿苯达唑驱虫治疗的反应。结果表明,驱虫显著降低了每克粪便中的虫卵数(EPG)。16S rRNA基因测序结果显示,驱虫后(某物种)肠道微生物群的丰富度和多样性显著增加。同时,驱虫治疗也改变了肠道微生物群的组成。在属水平上,(某些属名)在驱虫前样本中显著富集。(另一些属名)在驱虫后样本中显著富集。代谢组学分析显示,1865种代谢产物中有382种的相对丰度在驱虫前后样本之间存在显著差异。其中,103种代谢产物基于人类代谢组数据库(HMDB)进行了注释,主要分类为异戊二烯脂质、羧酸及其衍生物和有机氧化合物等。京都基因与基因组百科全书(KEGG)富集分析结果表明,这些代谢产物主要参与能量、氨基酸、脂质和嘌呤代谢。相关性分析表明,驱虫治疗后相对丰度上调的(某些菌属)与具有抗寄生虫活性的山奈酚、5,7 - 二羟基 - 3 - 甲氧基 - 4'- 异戊烯氧基黄酮、紫红素和大黄酸呈正相关。驱虫治疗后相对丰度下调的(某菌属)不仅与上述四种代谢产物呈负相关,还与维生素A的储存形式视黄醇β - 葡萄糖醛酸苷呈正相关,与增加宿主对(某些病原体)易感性的胞苷二磷酸胆碱呈正相关。

结论

本研究强调驱虫治疗对(某物种)肠道微生物群和代谢功能有影响。通过利用差异微生物群与代谢产物之间的相关性,可以探索潜在的益生菌或益生元,从而提高驱虫效率并降低其副作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/4a53ad47411b/fmicb-16-1581483-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/a2f265ef7c6f/fmicb-16-1581483-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/1392591fbc55/fmicb-16-1581483-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/d81e11174007/fmicb-16-1581483-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/950c9d086c0a/fmicb-16-1581483-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/b30f13205b4e/fmicb-16-1581483-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/4a53ad47411b/fmicb-16-1581483-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/a2f265ef7c6f/fmicb-16-1581483-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/a0a532faee9b/fmicb-16-1581483-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/1392591fbc55/fmicb-16-1581483-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/3c826a4f2dd5/fmicb-16-1581483-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/d81e11174007/fmicb-16-1581483-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/950c9d086c0a/fmicb-16-1581483-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/b30f13205b4e/fmicb-16-1581483-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5208/12058082/4a53ad47411b/fmicb-16-1581483-g008.jpg

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