In vitro fermentation characteristics of polysaccharide from Scrophularia ningpoensis and its effects on type 2 diabetes mellitus gut microbiota

Abstract

Background: Increasing evidence has shown a close relation between the pathogenesis of type 2 diabetes mellitus (T2DM), which is a global health problem with multifactorial etiopathogenesis, and gut microbiota.

Methods: During in-vitro fermentation of Scrophularia ningpoensis (known as Xuanshen) polysaccharide (SNP) by T2DM gut microbiota, effects of SNP on the gas content, production of short-chain fatty acids (SCFAs), metabolite profile and microbiota composition were studied.

Results: Analysis of chemical compositions indicates that the total sugar content of SNP was found to be as high as 87.35 ± 0.13% (w/w). SNP treatment significantly improved the gas volume and composition in T2DM fecal matter. Moreover, intestinal flora degraded SNP to produce SCFAs, thus regulating SCFA production and composition. Metabolomic analysis implied that SNP shows potential to regulate the five gut metabolites (L-valine, L-leucine, L-isoleucine, L-alanine, and xylitol) in T2DM fecal matter. Furthermore, dysbiosis of gut microbiota induced by T2DM was reversed by SNP. The evidence includes decreasing Firmicutes/Bacteroidota ratio at phylum level promoting proliferation of the bacterial abundance of Dorea, Parabacteroides, Faecalibacterium, and Lachnospira and decreased bacterial abundance of Escherichia-Shigella. Based on these findings, the action mechanism of SNP against T2DM was clarified by reshaping microbiota and regulating intestinal metabolites, and a novel target was provided for interventions of T2DM.

Keywords: Gut microbiota; Polysaccharide; Scrophularia ningpoensis; T2DM.

Figure 1. Effects of SNP upon the diversity of fecal microflora from humans.

(A) ACE, Chao, Shannon, and Simpson indices; Comparison of bacterial compositions across all groups based on (B) PCoA and (C) PLS-DA at the OTU level. Data are presented as means ± SDs (n = 8).

Figure 2. Bacterial taxonomic profiles at phylum levels.

Figure 3. Bacterial taxonomic profiles at genus levels.

Figure 4. Relative abundance of genera with a significant difference.

The importance of comparisons between indicated groups was evaluated by conducting Kruskal-Wallis tests on the significant difference, *P < 0.05, **P < 0.01, and ***P < 0.001.

Figure 5. Significant differences of microbiota across various groups were identified using LEfSe.

Figure 6. LDA scores of enriched bacterial taxa (LDA > 2.5 of LEfSe).

Figure 7. Gas production, methane (CH₄), carbon dioxide (CO₂), hydrogen (H₂) and hydrogen sulfide (H₂S) after 24-h in-vitro fermentation with T2DM human fecal Microflora.

One-way ANOVA was used to analyze results expressed as means ± SDs, and then post-hoc Tukey’s multiple comparisons tests were performed. *P < 0.05 and **P < 0.01.

Figure 8. Total SCFAs (acetic acid, butyric acid, propionic acid, isobutyric acid, isovaleric acid, and valeric acid) after 24-h in-vitro fermentation with T2DM human fecal microflora.

Data were expressed as means ± SDs (n = 8).

Figure 9. Metabolite profile after 24-h in-vitro fermentation with T2DM human fecal microflora.

(A) Score plots of PCA; (B) OPLS models; differential metabolite screening in (C) T2DM group vs. HC group, (D) HC+SNP group vs. HC group, and (E) T2DM+SNP group vs. T2DM group; (F) metabolic pathway analysis.

Figure 10. Correlation analysis of characteristic metabolites and bacteria.

Corr represents correlation. Red and blue separately denote positive and negative correlations. The darker the color, the stronger the correlation. *P < 0.05, **P < 0.01, and ***P < 0.001.