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葡聚糖硫酸钠诱导结肠炎小鼠肠道微生物群和代谢物的差异分析。

Differential analysis of intestinal microbiota and metabolites in mice with dextran sulfate sodium-induced colitis.

机构信息

Graduate School, Beijing University of Chinese Medicine, Beijing 100029, China.

Department of Gastroenterology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, China.

出版信息

World J Gastroenterol. 2022 Nov 21;28(43):6109-6130. doi: 10.3748/wjg.v28.i43.6109.

DOI:10.3748/wjg.v28.i43.6109
PMID:36483152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9724481/
Abstract

BACKGROUND

Intestinal micro-ecological imbalances impair the intestinal barrier and induce intestinal inflammation, for example, ulcerative colitis (UC). According to the latest research, abnormalities in intestinal microbiota structure and their metabolites play a dominant role in UC progression; in addition, they could affect the mucus barrier based on different factors. Although numerous studies have confirmed the important role of intestinal microbiota in UC pathogenesis, the intricate connection between microbiota and metabolites and mucus barrier in UC occurrence remains unclear, and correlation analyses of differential microbiota and their metabolites under UC are relatively scarce.

AIM

To reveal the differential intestinal microbiota and metabolites in UC pathogenesis and explore more sensitive biomarker compositions.

METHODS

We used the antibiotic combination method to establish intestinal pseudo-aseptic mice; afterward, dextran sulfate sodium (DSS) was applied to establish an acute experimental colitis mice model. Colitis severity, assessed based on disease activity index, colorectal length, colorectal wet weight, and histological lesions, and mucus-related staining (mucopolysaccharide alcian blue and immunofluorescence of mucin), was compared between the pseudo-aseptic and bacterial colitis mice. Finally, differential intestinal microbiota, metabolites, and their association and correlations, were analyzed by 16s rDNA sequencing in combination with non-targeted metabolomics, through gas chromatography-mass spectrometry.

RESULTS

Compared with the pseudo-aseptic mice, intestinal bacteria positive mice were more severely ill and their intestinal mucus loss was more pronounced in DSS-induced colitis ( < 0.05), suggesting that different microbiota and metabolites could cause the different degrees of colitis. Subsequently, we observed that in addition to , and , which were widely associated with colitis, , , , and may be involved in protection against colitis. Furthermore, differential metabolites of the microbiota were mainly enriched in the synthesis-related pathways of key structural sequences of mucin. In combination with the mucin-related staining and immunofluorescence results, the findings indicate that the differential microbiota and their metabolites potentially regulate the composition and function of mucus under colitis.

CONCLUSION

Microbiota and their metabolites are major factors regulating the composition and function of mucus, in turn influencing the function and structure of intestinal mucus barrier under colitis. The different microbiota and metabolites identified in the present study could be novel biomarkers for colitis.

摘要

背景

肠道微生态失衡会损害肠道屏障并引发肠道炎症,例如溃疡性结肠炎(UC)。根据最新研究,肠道微生物群落结构及其代谢物的异常在 UC 进展中起主导作用;此外,它们可能会基于不同因素影响黏液屏障。尽管大量研究证实了肠道微生物群在 UC 发病机制中的重要作用,但 UC 发病过程中微生物群及其代谢物与黏液屏障之间的复杂联系仍不清楚,UC 下差异微生物群及其代谢物的相关性分析也相对较少。

目的

揭示 UC 发病机制中差异肠道微生物群和代谢物,并探索更敏感的生物标志物组成。

方法

我们使用抗生素联合方法建立肠道假无菌小鼠;随后,应用葡聚糖硫酸钠(DSS)建立急性实验性结肠炎小鼠模型。通过疾病活动指数、结肠直肠长度、结肠直肠湿重和组织学病变以及黏液相关染色(黏多糖阿尔辛蓝和黏蛋白免疫荧光)比较假无菌和细菌结肠炎小鼠的结肠炎严重程度。最后,通过 16s rDNA 测序结合非靶向代谢组学,通过气相色谱-质谱分析,分析差异肠道微生物群、代谢物及其相关性。

结果

与假无菌小鼠相比,肠道细菌阳性小鼠在 DSS 诱导的结肠炎中病情更严重,肠道黏液丢失更明显(<0.05),提示不同的微生物群和代谢物可能导致不同程度的结肠炎。随后,我们观察到除了与结肠炎广泛相关的、和 外,、、、和 可能参与了对结肠炎的保护。此外,微生物群的差异代谢物主要富集在黏蛋白关键结构序列的合成相关途径中。结合黏液相关染色和免疫荧光结果,表明差异微生物群及其代谢物可能在结肠炎下调节黏液的组成和功能。

结论

微生物群及其代谢物是调节黏液组成和功能的主要因素,进而影响结肠炎下肠道黏液屏障的功能和结构。本研究中鉴定的差异微生物群及其代谢物可能是结肠炎的新型生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/aecd018d0b70/WJG-28-6109-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/b24cd35bb59a/WJG-28-6109-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/264fe976a8c9/WJG-28-6109-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/e78e1bbd2e19/WJG-28-6109-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/2e4e53647c01/WJG-28-6109-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/5c69758d5fb0/WJG-28-6109-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/aecd018d0b70/WJG-28-6109-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/b24cd35bb59a/WJG-28-6109-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/264fe976a8c9/WJG-28-6109-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/e78e1bbd2e19/WJG-28-6109-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/2e4e53647c01/WJG-28-6109-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/5c69758d5fb0/WJG-28-6109-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/30f2/9724481/aecd018d0b70/WJG-28-6109-g006.jpg

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