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. 2024 Jul 30;10(15):e35461.
doi: 10.1016/j.heliyon.2024.e35461. eCollection 2024 Aug 15.

TMAO is involved in kidney-yang deficiency syndrome diarrhea by mediating the "gut-kidney axis"

Affiliations

TMAO is involved in kidney-yang deficiency syndrome diarrhea by mediating the "gut-kidney axis"

Shiqin Xie et al. Heliyon. .

Abstract

Background: Trimethylamine-N-oxide (TMAO) is a harmful metabolite dependent on the intestinal microbiota and excreted through the kidneys. According to numerous investigations, rich circulation concentrations of TMAO have been linked to kidney and gastrointestinal disorders. Through the "gut-kidney axis" mediated by TMAO, this research attempted to clarify the microbiological causes of kidney-yang deficiency syndrome diarrhea.

Methods: Adenine and Folium Sennae were used to create a mouse model of kidney-yang deficiency syndrome diarrhea. 16S rRNA sequencing was used to identify the traits of the intestinal mucosal microbiota. ELISA was used to assess TMAO, transforming growth factor-β1 (TGF-β1), interleukin-1β (IL-1β), and NOD-like receptor thermal protein domain associated protein 3 (NLRP3). Kidney tissue fibrosis was evaluated using Masson's trichrome staining, and immunohistochemical labeling was used to investigate the protein expression of occludin and Zonula Occludens-1(ZO-1) in small intestine tissue. Microbial activity was determined by using fluorescein diacetate (FDA) hydrolysis spectrophotometry.

Results: TMAO showed a positive correlation with NLRP3, IL-1β and TGF-β1, all of which exhibited substantial increases (P < 0.05). Significant renal fibrosis and decreased ZO-1 and occludin expression in small intestine tissues were detected in the model group. The sequencing results revealed alterations in both α and β diversities of small intestinal mucosal microbiota. Elevated TMAO concentrations were potentially associated with increasing Firmicutes/Bacteroidota (F/B) ratios, Streptococcus, Pseudomonas and unclassified Clostridia UCG 014, but with decreasing Rothia and RB41 abundances.

Conclusion: This study establishes a link between intestinal microbiota dysbiosis and elevated TMAO concentrations. TMAO can activate inflammatory responses and cytokines, contributing to kidney-yang deficiency syndrome diarrhea via the "gut-kidney axis". Moreover, TMAO may coincide with disruptions in the intestinal barrier and renal fibrosis. Dysfunction of the "gut-kidney axis" further elevates TMAO levels, perpetuating a vicious cycle.

Keywords: Gut-kidney axis; Inflammation; Intestinal barrier; Intestinal microbiota; Kidney-yang deficiency syndrome diarrhea; Renal fibrosis; TMAO.

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Conflict of interest statement

The authors declare that they have no competing interests. All the authors have approved the manuscript and agree with this submission.

Figures

Fig. 1
Fig. 1
General behavioral observations and symptoms of the mice. Note: (A) Activity status, (B) Mental status, (C) Average food intake, (D) Average water intake, (E) Anal temperature, (F) Weight changes. The values were expressed as mean ± standard deviation (n = 7 for each group). *P < 0.05, ***P < 0.001.
Fig. 2
Fig. 2
Effect of modeling on fecal characteristics and organ indices. Note: (A) Fecal characteristics, (B) Cage box humidity, (C) Perianal cleanliness, (D) Fecal water content, (E) Spleen index, (F) Thymus index. The values were expressed as mean ± standard deviation (n = 7 for each group). *P < 0.05.
Fig. 3
Fig. 3
(A) Changes in microbial activity, (B)Trimethylamine-N-oxide levels in serum, (C) Trimethylamine-N-oxide levels in kidney tissue, (D) Trimethylamine-N-oxide levels in small intestine tissue, (E) NOD-like receptor thermal protein domain associated protein 3 levels in serum, (F) Interleukin-1β levels in serum, (G) Transforming growth factor-β1 levels in serum. The values were expressed as mean ± standard deviation (Figure A: n = 3 for each group; Figure B–G: n = 6 for each group). *P < 0.05, ***P < 0.001.
Fig. 4
Fig. 4
Effect of modeling on the intestinal barrier. Note: (A) Effect of the model on renal fibrosis (Masson staining, × 400), (B) area of renal fibrosis (Masson semiquantitative), (C) Zonula Occludens-1 protein expression in intestinal tissue (immunohistochemistry × 100, × 400), (D) Zonula Occludens-1 average optical density, (E) Occludin protein expression in intestinal tissue (immunohistochemistry × 100, × 400), (F) Occludin average optical density. The values were expressed as mean ± standard deviation (n = 3 for each group). **P < 0.01.
Fig. 5
Fig. 5
Diversity analysis of the intestinal intestinal microbiota. Note: (A) Angiotensin-converting enzyme index, (B) Chao1 index, (C) Shannon index, (D) Simpson index, (E) Principal coordinates analysis, (F) Non-metric multidimensional scaling analysis. The values were expressed as mean ± standard deviation (n = 6 for each group).
Fig. 6
Fig. 6
Structural changes in the intestinal intestinal microbiota. Note: (A) Venn plot of Amplicon Sequence Variants. (B) Interaction yuk jak plot, (C) Phylum-level relative abundance plot, (D) Phylum-level dominant intestinal microbiota, (E) Genus-level relative abundance plot, (F) Genus-level dominant intestinal microbiota. The values were expressed as mean ± standard deviation (n = 6 for each group). **P < 0.01.
Fig. 7
Fig. 7
Characteristics of the intestinal microbiota. Note: (A) Evolutionary branching diagrams, (B) distribution bar charts, (C) subordination tracing Sankey diagrams (n = 6 for each group).
Fig. 8
Fig. 8
Functional analysis of the intestinal microbiota. Note: (A) Tracking Sankey plots (Level 1 and Level 2), (B) Functional predictive abundance plots (Level 2 and Level 3), (C) Metabolic function intergroup comparative box line plots (Level 3). The values were expressed as mean ± standard deviation (n = 6 for each group).
Fig. 9
Fig. 9
Correlation analysis. Note: (A) RDA redundancy analysis of mucosal genera associated with trimethylamine-N-oxide, transforming growth factor-β1, interleukin-1β and NOD-like receptor thermal protein domain associated protein 3; (B) RDA redundancy analysis of trimethylamine-N-oxide combined with transforming growth factor-β1, interleukin-1β and NOD-like receptor thermal protein domain associated protein 3; (C) scatter plot of the correlation between trimethylamine-N-oxide and NOD-like receptor thermal protein domain associated protein 3; (D) scatter plot of the correlation between trimethylamine-N-oxide and interleukin-1β; (E) scatter plot of the correlation between trimethylamine-N-oxide and transforming growth factor-β1 (n = 6 for each group).

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