Faecal and mucosal microbiota in patients with functional gastrointestinal disorders: Correlation with toll-like receptor 2/toll-like receptor 4 expression

World Journal of Gastroenterology : WJG
Li-Na DongYi Han

Abstract

To investigate the intestinal luminal microbiota (LM) and mucosa-associated microbiota (MAM) in Chinese patients with functional gastrointestinal disorders (FGIDs) and examine the association between these communities and the expression of toll-like receptor (TLR) 2 and TLR4. Thirty-two Chinese subjects who suffered from symptoms of FGIDs, as confirmed by gastroenterologists, were enrolled in this study. Fresh faecal samples and descending colonic mucosal biopsies were collected from the subjects before (faecal) and during (mucosal) flexible colonoscopy. For analysis of the samples, we performed high-throughput sequencing of the V3-V4 region of the 16S rRNA gene and reverse transcription (RT)-PCR to detect the expression of colonic TLR2 and TLR4. Differences in the stool and mucosal microbiota were examined and a correlation network analysis was performed. The microbiota of faecal samples was significantly more diverse and richer than that of the mucosal samples, and the LM and MAM populations differed significantly. TLR2 expression showed a significant positive correlation with TLR4 expression. In the MAM samples, the genera Faecalibacterium and Ruminococcus, which belong to the family Ruminococcaceae, were inversely correlated ...Continue Reading

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Citations

Feb 1, 2018·International Journal of Molecular Sciences·Valeria D'Argenio
Sep 22, 2018·Journal of Crohn's & Colitis·Miranda G KiernanColum P Dunne
May 22, 2020·Frontiers in Microbiology·Xuewei WangYuan Fan
Jun 2, 2018·Journal of Immunology Research·Lifang Zhao, Zhaoying Fu
Aug 5, 2019·Clinica Chimica Acta; International Journal of Clinical Chemistry·Li ZhangFaming Pan
May 19, 2021·International Journal of Food Sciences and Nutrition·Xin ChenYuanyin Wang

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Methods Mentioned

BETA
biopsies
biopsy

Software Mentioned

SPSS
Quantitative Insights Into Microbial Ecology ( QIIME )
packages
UPARSE
R
FLASH

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