某种肠道细菌
生物
肠道菌群
小桶
阿克曼西亚
内科学
乳酸菌
免疫学
生物化学
医学
基因表达
转录组
基因
发酵
作者
Xuanxin Lyu,Ming Jiang,Jiahao Shi,Qi Liu,Xilian Liu,Yulan Li,Shu‐Qin Ding,Xianpeng Dai
出处
期刊:PeerJ
[PeerJ, Inc.]
日期:2025-04-07
卷期号:13: e19222-e19222
摘要
Background In recent years, a novel animal abdominal aortic aneurysm (AAA) model was established by administering erythropoietin (EPO) to wild-type (WT) mice. However, the influence of EPO on the murine fecal microbiota remains uninvestigated. Therefore, this study aims to explore the potential association between gut microbiota changes and AAA development in this model. Methods and results Adult male C57BL/6 mice were used to establish the AAA model by intraperitoneal administration of recombinant human EPO at a dosage of 10,000 IU/kg daily for 28 consecutive days. Hematoxylin and eosin (H&E) and Elastin Van Gieson (EVG) staining revealed that EPO administration increased aortic wall thickness and diameter, accompanied by enhanced degradation of the elastic lamina. The 16S rRNA—sequencing data were deposited in the Sequence Read Archive (PRJNA1172300). LEfSe analysis revealed that Akkermansia, Lawsonibacter, Clostridium, and Neglectibacter were significantly associated with EPO-induced AAA development, while Lactobacillus, Alistipes, Limosilactobacillus, and Eisenbergiella showed significant negative correlations. Analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) prediction module revealed significant differences in metabolic pathways between the two groups, including alanine, aspartate and glutamate metabolism; cysteine and methionine metabolism; pyrimidine metabolism; carbon metabolism; ABC transporters; and oxidative phosphorylation pathways. Conclusions EPO-induced gut dysbiosis, particularly changes in Akkermansia, Lactobacillus, and Alistipes abundance, may contribute to AAA formation via inflammation, oxidative stress, and metabolic dysfunction. While this model advances AAA research, its limitations underscore the need for human validation and mechanistic studies. Future work should prioritize multi-omics integration and cross-model comparisons to unravel the complex microbiota-AAA axis.
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