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Comparative Study
. 2020 Aug 27;18(9):444.
doi: 10.3390/md18090444.

Sargassum fusiforme Polysaccharides Prevent High-Fat Diet-Induced Early Fasting Hypoglycemia and Regulate the Gut Microbiota Composition

Affiliations
Comparative Study

Sargassum fusiforme Polysaccharides Prevent High-Fat Diet-Induced Early Fasting Hypoglycemia and Regulate the Gut Microbiota Composition

Bin Wei et al. Mar Drugs. .

Abstract

A low fasting blood glucose level is a common symptom in diabetes patients and can be induced by high-fat diet (HFD) feeding at an early stage, which may play important roles in the development of diabetes, but has received little attention. In this study, five polysaccharides were prepared from Sargassumfusiforme and their effects on HFD-induced fasting hypoglycemia and gut microbiota dysbiosis were investigated. The results indicated that C57BL/6J male mice fed an HFD for 4 weeks developed severe hypoglycemia and four Sargassumfusiforme polysaccharides (SFPs), consisting of Sf-2, Sf-3, Sf-3-1, and Sf-A, significantly prevented early fasting hypoglycemia without inducing hyperglycemia. Sf-1 and Sf-A could also significantly prevent HFD-induced weight gain. Sf-2, Sf-3, Sf-3-1, and Sf-A mainly attenuated the HFD-induced decrease in Bacteroidetes, and all five SFPs had a considerable influence on the relative abundance of Oscillospira, Mucispirillum, and Clostridiales. Correlation analysis revealed that the fasting blood glucose level was associated with the relative abundance of Mucispinllum and Oscillospira. Receiver operating characteristic analysis indicated that Mucispinllum and Oscillospira exhibited good discriminatory power (AUC = 0.745-0.833) in the prediction of fasting hypoglycemia. Our findings highlight the novel application of SFPs (especially Sf-A) in glucose homeostasis and the potential roles of Mucispinllum and Oscillospira in the biological activity of SFPs.

Keywords: Sargassum fusiforme polysaccharides; early fasting hypoglycemia; gut microbiota; high-fat diet.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Effects of S. fusiforme polysaccharides on the (A) body weight, (B) fasting blood glucose, (C) oral glucose tolerance test (OGTT), (D) liver, (E) epididymal fat, and (F) pancreas weight in high-fat diet (HFD)-treated mice. Values are the mean ± SD (n = 10). * p < 0.05, ** p < 0.01, and *** p < 0.001 vs. blank. # p < 0.05, ## p < 0.01, and ### p < 0.001 vs. control.
Figure 2
Figure 2
Effects of S. fusiforme polysaccharides on the composition and α-diversity of the gut microbiota in HFD-treated mice. (A) Gut microbiota composition at the phylum level, (B) Abundance-based Coverage Estimator (ACE) metric, (C) Chao1 diversity index, (D) Simpson’s diversity index, and (E) Shannon’s diversity index of the gut microbiota. Values are the mean ± SD (n = 10). *** p < 0.001 vs. blank. # p < 0.05 vs. control.
Figure 3
Figure 3
Effects of S. fusiforme polysaccharides on the relative abundance of (A) Bacteroidetes, (B) Firmicutes, (C) Proteobacteria, (D) Actinobacteria, (E) Deferribacteres, and (F) Verrucomicrobia in the gut microbiota in HFD-treated mice. Values are the mean ± SD (n = 10). * p < 0.05, ** p < 0.01, and *** p < 0.001 vs. blank. # p < 0.05, ### p < 0.001 vs. control.
Figure 4
Figure 4
Effects of S. fusiforme polysaccharides on the relative abundance of (A) o_Clostridiales._._, (B) g_Oscillospira, (C) g_Mucispirillum, (D) f_Coriobacteriaceae.g_, (E) g_Moryella, and (F) g_Bifidobacterium in the gut microbiota in HFD-treated mice. Values are the mean ± SD (n = 10). * p < 0.05, ** p < 0.01, and *** p < 0.001 vs. blank. # p < 0.05, ## p < 0.01, and ### p < 0.001 vs. control.
Figure 5
Figure 5
Effects of S. fusiforme polysaccharides on the (A) gut microbiota composition at the genus level, (B) predicted functional gene, (C) metabolic pathway coverage, and (D) abundance in HFD-treated mice.
Figure 6
Figure 6
(A) Correlations between the fasting blood glucose level and the relative abundance of gut microbiota. A color key is shown at the bottom right of the heatmap to demonstrate the size of the correlation coefficient. Values in each lattice represent the correlation coefficients. * False discovery rate (FDR)-corrected p-value < 0.05; ** FDR-corrected p-value < 0.01; *** FDR-corrected p-value < 0.05. NA, not applicable. (B) Fitting receiver operating characteristic (ROC) curves of g_Oscillospira, g_Bifidobacterium, f_Coriobacteriaceae.g_, and g_Mucispinllum for the prediction of fasting hypoglycemia.

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