The effects of candidate probiotic strains on the gut environment in dextran sulfate sodium-induced colitis mouse

Abstract

Inflammatory bowel disease (IBD) is a chronic condition characterized by intestinal inflammation and dysbiosis, with limited treatment options and significant challenges in long-term management. This study investigated the therapeutic potential of novel strains belonging to Bifidobacterium longum and Limosilactobacillus species, in a dextran sodium sulfate (DSS)-induced mouse model of colitis. In this study, our primary objective was to determine whether ingestion of these strains alleviates colitis symptoms and, if so, to elucidate how they restored gut microbial balance and modulated microbial metabolic functions. In most probiotic-treated groups, colitis disease activity index scores were significantly improved and colon length was preserved, with strains CBA7106 and BBH exhibiting efficacy comparable to that of the Lactobacillus rhamnosus GG (used as a positive control). Moreover, histological analyses confirmed reduced inflammation and enhanced mucosal integrity. Microbial diversity assessments demonstrated a marked restoration of gut microbial composition, highlighted by increased abundances of beneficial taxa such as Lactobacillus and Akkermansia. Metabolomic profiling identified key anti-inflammatory metabolites, including 6-hydroxycaproic acid, indole-3-lactic acid, and choline, which were significantly elevated in the probiotic-treated groups. Notably, functional analyses using PICRUSt2 revealed a sustained decrease in the siderophore biosynthesis pathway (ko01053), suggesting that these candidate probiotic strains may inhibit siderophore production-a pivotal mechanism by which pathogenic bacteria aggravate intestinal inflammation. Taken together, these findings indicate that the candidate probiotic strains CBA7106 and BBH effectively mitigate DSS-induced colitis by modulating the gut microbiota, promoting the production of anti-inflammatory metabolites, and suppressing siderophore biosynthesis. This study provides valuable insights into the development of targeted probiotic therapies for IBD, underscoring their potential as a complementary approach to restoring intestinal health and reducing inflammation. Further clinical studies are warranted to validate these observations in human populations.

Keywords: Candidate probiotic strains; Colitis; Dextran sulfate sodium; Gut microbiota; Inflammatory bowel disease.

Fig. 1

Schematic representation of the experimental design for DSS-induced colitis and probiotic administration in mice. Acute colitis was induced in mice by administering dextran sulfate sodium (DSS) in drinking water for 5 days (days 0–5), followed by a 7-day washout and recovery period (days 5–12). Candidate probiotic strains were orally administered during the recovery phase (days 12–17), and all animals were sacrificed on day 17. The experimental groups included: Sham (no DSS or probiotic), DSS control (DSS-CON), positive control (Lactobacillus rhamnosus GG; DSS-LGG), Bifidobacterium longum (DSS-BBH), Lacticaseibacillus paracasei (DSS-CBA7104), Limosilactobacillus fermentum (DSS-CBA7106), and Lactobacillus gasseri (DSS-CBA7108).

Fig. 2

Differences in disease activity index scores and colon length in DSS-induced colitis mice following probiotic administration. (A) Disease activity index score. (B) Colon length measurements at the endpoint of the experiment. (C) Body weight changes in DSS-induced colitis mice treated with candidate probiotic strains. Statistical comparisons were made using two-way ANOVA followed by Tukey’s multiple comparisons test. p < 0.05, p < 0.01, p < 0.001, p < 0.0001; ns = not significant. (D) Statistical comparison of colon length. All data presented as the mean (M) ± standard deviation (S.D.). ‡p < .01, vs. Sham; *p < .05, vs. DSS-CON.

Fig. 3

Histological evaluation of colonic damage and corresponding histology scores in DSS-induced colitis mice. (A) Representative hematoxylin and eosin (H&E) stained colon sections from each group: Sham, DSS-CON, DSS-LGG, DSS-CBA7104, DSS-CBA7106, DSS-CBA7108, and DSS-BBH. DSS treatment caused substantial epithelial disruption, crypt loss, and inflammatory cell infiltration, which were partially restored in probiotic-treated groups. Scale bars = 100 μm. (B) Quantitative histology scores based on epithelial integrity, crypt architecture, and inflammatory cell infiltration. Data are presented as mean ± SEM (n = 6 per group). Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test. p < 0.05, p < 0.01, p < 0.001.*p < .0001, vs. Sham; ***p < .001, ****p < .0001, vs. DSS-CON.

Fig. 4

Metabolomics of the culture medium following the cultivation of strains exhibiting colitis-alleviating effect. (A) The Venn diagram of differential metabolites identified by univariate statistical analyses. (B) The pattern of metabolic phenotype with hierarchical clustering analysis.

Fig. 5

Gut microbial diversity in a DSS-induced colitis mouse model following administration of a candidate probiotic strains. (A) Alpha diversity; black bar = Sham, orange bar = DSS-CON, brown bar = 5 days after DSS-CON; red bar = 17 days after DSS-CON, blue bar = DSS-LGG, light blue bar = DSS-BBH, and green = DSS-CBA7106. From left, observed features, Shannon index, and Pielou’s evenness index are shown respectively. (B) Beta diversity. (C) Bar plot showing significant differences for each group based on the 5th day after DSS treatment.

Fig. 6

The genus-level relative abundances and heatmap of LefSe analysis results comparing probiotic-treated groups following administration of novel probiotic strains in a DSS-induced colitis mouse model. The Fig. 6A shows the relative abundances of microbial genera according to the DSS administration schedule, while Fig. 6B presents a heatmap of LefSe analysis results comparing the groups. The red and blue colors represent the comparison groups, respectively.

Fig. 7

Predicted gut microbial functions of novel probiotic strains showing ameliorative effects on DSS-induced colitis. (A) The Venn diagram showing common KOs among predicted KOs after treatment with each probiotic (B) Heatmap for significantly different KOs by group analyzing gut microorganism.