Fufang Taizishen Granules Attenuate Chemotherapy-Induced Intestinal Mucositis by Modulating Gut Microbiota and Amino Acid Metabolism

Abstract

Chemotherapy-induced intestinal mucositis is a severe adverse effect affecting cancer patients, and there are currently no effective strategies for its prevention. Fufang Taizishen granules (FFTZS), a traditional Chinese medicine (TCM) known for its anti-inflammatory, anti-fatigue, and immunostimulatory properties, have shown therapeutic potential. However, the effects of FFTZS on chemotherapy-induced intestinal mucositis and its underlying mechanisms remain unclear. A mouse model of intestinal mucositis was induced using 5-FU and irinotecan to assess the protective effects of FFTZS. The study found that FFTZS enhanced food intake, reduced diarrhea index, and improved histopathological damage in colonic tissues. FFTZS also reduced inflammatory cell infiltration and inhibited apoptosis. Moreover, FFTZS treatment increased the expression of Claudin-1 and ZO-1 proteins. Microbial analysis revealed an enrichment of beneficial bacteria and a reduction of opportunistic pathogens, whereas metabolomic analysis showed that FFTZS corrected amino acid metabolic disturbances induced by chemotherapy. These findings suggest that FFTZS mitigates chemotherapy-induced intestinal mucositis by preserving mucosal integrity, modulating gut microbiota, and restoring metabolic homeostasis.

Keywords: Fufang Taizishen granules; amino acid metabolism; gut microbiota; intestinal mucositis.

FIGURE 1

Schematic representation of the experimental design (A) and changes in food intake (B), diarrhea index (C), and weight loss (D) of mice in different treatment groups.

FIGURE 2

Effects of FFTZS on colonic tissue morphology and inflammatory infiltration in chemotherapy‐treated mice. (A) H&E staining of colonic tissue. FFTZS effects on colonic length (B), villus length (C), crypt depth (D), and villus length‐to‐crypt depth ratio (E). FFTZS effects on MPO (F) and EPO (G) levels in colonic tissue, as well as serum IL‐10 (H) and IL‐17 (I) levels. Data are presented as mean ± SD (n = 6). ^# p < 0.05, ^## p < 0.01 versus CON group; *p < 0.05, **p < 0.01 versus MOD group.

FIGURE 3

Effects of FFTZS on the colonic immune barrier in chemotherapy‐treated mice. FFTZS effects on (A) goblet cells and (B) mucus layer in colonic tissue. FFTZS effects on IgA (C) and sIgA (D) levels in colonic tissue, and serum IL‐10 (E) and IL‐17 (F) levels. Data are presented as mean ± SD (n = 6). ^## p < 0.01 versus CON group; **p < 0.01 versus MOD group.

FIGURE 4

Effects of FFTZS on apoptosis in colonic tissue of chemotherapy‐treated mice.

FIGURE 5

Effects of FFTZS on the expression of Claudin‐1 and ZO‐1 proteins in colonic tissue of chemotherapy‐treated mice.

FIGURE 6

FFTZS improves gut microbiota composition in 5‐FU and irinotecan‐treated mice. (A) Manhattan plot showing enriched and depleted microbial taxa between different treatment groups. (B) Principal component analysis (PCA), with PCoA1 and PCoA2 representing the two most significant factors influencing microbial distribution. (C) Microbial community stacked bar plot. Analysis of microbial niche width (D) and average variation degree (E) among treatment groups. (F) Microbial diversity analysis. Data are presented as mean ± SD (n = 5). ^# p < 0.05, ^## p < 0.01 versus CON group; *p < 0.05, **p < 0.01 versus MOD group.

FIGURE 7

Effects of FFTZS on the metabolic profile of gut microbiota in chemotherapy‐treated mice. (A) OPLS‐DA score plot for CON versus MOD, (B) MOD versus EI, and (C) CON versus EI. (D) Volcano plot of differential metabolites between CON and MOD groups. (E) Volcano plot of differential metabolites between MOD and EI groups. (F) Venn diagram of overlapping differential metabolites.

FIGURE 8

FFTZS alleviates metabolic disturbances in the gut microbiota of chemotherapy‐treated mice. (A) KEGG enrichment pathway analysis based on metabolomics. FFTZS effects on fecal concentrations of (B) amino acids, (C) fatty acids, (D) carbohydrates, (E) carbonyl compounds, (F) sesquiterpenoids, and (G) monoterpenoids. (H) Heatmap of 14 amino acid metabolites among different treatment groups. #p < 0.05, ##p < 0.01 versus CON group; *p < 0.05, **p < 0.01 versus MOD group.

FIGURE 9

Correlation analysis between gut microbiota and amino acid metabolism. Correlations of Roseburia with L‐serine (A) and L‐tyrosine (B), Peptococcus with L‐serine (C), and Candidatus Saccharimonas with L‐phenylalanine (D).

FIGURE 10

Redundancy analysis of gut microbiota composition and host metabolic parameters.