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. 2021 Aug 4;16(8):e0255651.
doi: 10.1371/journal.pone.0255651. eCollection 2021.

Structural and quantitative alterations of gut microbiota in experimental small bowel obstruction

Affiliations

Structural and quantitative alterations of gut microbiota in experimental small bowel obstruction

Jiali Mo et al. PLoS One. .

Abstract

Objective: To investigate structural and quantitative alterations of gut microbiota in an experimental model of small bowel obstruction.

Method: A rat model of small bowel obstruction was established by using a polyvinyl chloride ring surgically placed surrounding the terminal ileum. The alterations of gut microbiota were studied after intestinal obstruction. Intraluminal fecal samples proximal to the obstruction were collected at different time points (24, 48 and 72 hours after obstruction) and analyzed by 16s rDNA high-throughput sequencing technology and quantitative PCR (qPCR) for target bacterial groups. Furthermore, intestinal claudin-1 mRNA expression was examined by real-time polymerase chain reaction analysis, and serum sIgA, IFABP and TFF3 levels were determined by enzyme-linked immunosorbent assay.

Results: Small bowel obstruction led to significant bacterial overgrowth and profound alterations in gut microbiota composition and diversity. At the phylum level, the 16S rDNA sequences showed a marked decrease in the relative abundance of Firmicutes and increased abundance of Proteobacteria, Verrucomicrobia and Bacteroidetes. The qPCR analysis showed the absolute quantity of total bacteria increased significantly within 24 hours but did not change distinctly from 24 to 72 hours. Further indicators of intestinal mucosa damage and were observed as claudin-1 gene expression, sIgA and TFF3 levels decreased and IFABP level increased with prolonged obstruction.

Conclusion: Small bowel obstruction can cause significant structural and quantitative alterations of gut microbiota and induce disruption of gut mucosa barrier.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. The general condition of the rats.
Body weight (A), food intake (B), water intake (C), intestinal diameter (D) of the rats. Data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.
Fig 2
Fig 2. Histological micrographs of intestinal tissue sections and intestinal mucosal damage scores.
Intestinal sections were assessed by H&E staining (A-D). Intestinal mucosal injury was quantified by Chiu’s scores (H). Data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.
Fig 3
Fig 3. Principal coordinate analysis (PCoA) analysis before surgery.
Fig 4
Fig 4. Alpha diversity of fecal contents from sham and obstruction rats at different time points.
Observed species (A), Chao1 (B), Shannon (C), Coverage (D) of the gut microbiomes. The data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.
Fig 5
Fig 5
The plots of principal component analysis (PCA) (A) and principal coordinate analysis (PCoA) based on unweighted UniFrac distance metric (B). Samples of rats were presented by different color-filled symbols. Analysis of similarity revealed clustering among rats with obstruction and sham-operated rats.
Fig 6
Fig 6. Comparison of small intestinal microbiota composition in sham and SBO rats.
Intestinal microbiota composition at Phylum level (A), Genus level (B) are shown in the figure.
Fig 7
Fig 7. Comparison of relative abundances of the bacterial taxa exhibiting significant changes in sham and SBO rats.
Relative abundances of the bacteria at Phylum level (A), Genus level (B) are shown in the figure. Data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.
Fig 8
Fig 8. Heatmap analysis at the genus level among four groups.
Fig 9
Fig 9. LEfSe analysis for identification of differentially abundant taxa in SBO compared to sham rats.
The length of the horizontal bar represents the LDA score in log scale, and only taxa meeting an LDA score threshold > 4.0 are listed.
Fig 10
Fig 10. Total volume of fecal contents and changes in quantification of target bacterial groups with prolonged obstruction time.
Data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.
Fig 11
Fig 11. Changes in indicators of intestinal mucosal barrier function.
Data are presented as the mean ± SD, n = 5. * P<0.05, ** P<0.01 vs. Sham group; #P<0.05, ## P<0.01 vs. the preceding group.

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