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SCIENCE CHINA Life Sciences, https://doi.org/10.1007/s11427-019-1647-6

Hypoglycemic mechanism of polysaccharide from Cyclocarya paliurus leaves in type 2 diabetic rats by gut microbiota and host metabolism alteration

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  • ReceivedNov 3, 2019
  • AcceptedFeb 7, 2020
  • PublishedJun 17, 2020

Abstract

Diabetes mellitus is a serious threat to human health. Cyclocarya paliurus (Batal.) Iljinskaja (C. paliurus) is one of the traditional herbal medicine and food in China for treating type 2 diabetes, and the C. paliurus polysaccharides (CP) were found to be one of its major functional constituents. This research aimed at investigating the hypoglycemic mechanism for CP. It was found that CP markedly attenuated the symptoms of diabetes, and inhibited the protein expression of Bax, improved the expression of Bcl-2 in pancreas of diabetic rats, normalized hormones secretion and controlled the inflammation which contributed to the regeneration of pancreatic β-cell and insulin resistance. CP treatment increased the beneficial bacteria genus Ruminococcaceae UCG-005 which was reported to be a key genus for protecting against diabetes, and the fecal short-chain fatty acids levels were elevated. Uric metabolites analysis showed that CP treatment helped to protect with the diabetes by seven significantly improved pathways closely with the nutrition metabolism (amino acids and purine) and energy metabolism (TCA cycle), which could help to build up the intestinal epithelial cell defense for the inflammation associated with the diabetes. Our study highlights the specific mechanism of prebiotics to attenuate diabetes through multi-path of gut microbiota and host metabolism.


Funded by

the National Natural Science Foundation of China for Distinguished Young Scholars(31825020)

the Outstanding Science and Technology Innovation Team Project in Jiangxi Province(20165BCB19001)

the Project of Academic Leaders of the Major Disciplines in Jiangxi Province(20162BCB22008)

the Young Key Project of Natural Science Foundation of Jiangxi Province(20171ACB21013)

the Collaborative Project in Agriculture and Food Field between China and Canada(2017ZJGH0102001)

and the Research Project of State Key Laboratory of Food Science and Technology(SKLF-ZZA-201611)


Acknowledgment

This work was supported by the National Natural Science Foundation of China for Distinguished Young Scholars (31825020), the Outstanding Science and Technology Innovation Team Project in Jiangxi Province (20165BCB19001), the Project of Academic Leaders of the Major Disciplines in Jiangxi Province (20162BCB22008), the Young Key Project of Natural Science Foundation of Jiangxi Province (20171ACB21013), the Collaborative Project in Agriculture and Food Field between China and Canada (2017ZJGH0102001), and the Research Project of State Key Laboratory of Food Science and Technology (SKLF-ZZA-201611). We thank all the volunteers for their help in collecting samples of animal tissues and feces.


Interest statement

The author(s) declare that they have no conflict of interest.


Supplement

SUPPORTING INFORMATION

The supporting information is available online at https://doi.org/10.1007/s11427-019-1647-6. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.


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  • Figure 1

    A, Design of the animal trial. Effect of CP on FBG (B), insulin levels and insulin sensitivity (C–E) of rats. DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW). Data were expressed as the mean±SD (n=10). *P<0.05, **P<0.01 compared with the DC group; #P<0.05, ##P<0.01 compared with the NC group. The dose of CP was used according to our previous study.

  • Figure 2

    Effect of CP on inflammatory cytokines IL-1β, IL-6 and TNF-α levels (A), leptin (B), adiponectin (C) and GLP-1 levels (D). Influence of CP on SCFAs contents (E), moisture contents (F), and pH (G) in the colon feces of rats. NC, non-diabetic control; DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW). Data were expressed as the mean±SD (n=10). *P<0.05, **P<0.01 compared with the DC group; #P<0.05, ##P<0.01 compared with the NC group.

  • Figure 3

    Effect of CP on pathology and expression of apoptosis related proteins of pancreas. A, H&E staining. Scale bar, 200 μm. B, Bax. Scale bar, 50 μm. C, Bcl-2. Scale bar, 50 μm. D, IOD value of Bax and Bcl-2. NC, non-diabetic control; DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW). Data were expressed as the mean±SD (n=10). *P<0.05, **P<0.01 compared with the DC group; #P<0.05, ##P<0.01 compared with the NC group. The white, red, and black arrows annotate the islet, Bax, and Bcl-2, respectively.

  • Figure 4

    (Color online) Bacterial main communities at the genus level (A) and phylum level (B) in the colon feces of rats. Data showed the average percentage of total identified sequences obtained from samples. Only the bacterial taxa representing at least 1% of total identified sequences are presented. C and D, Alpha diversity indexes for microbiota in the colon feces of rats. NC, non-diabetic control; DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW).

  • Figure 5

    (Color online) A and B, LEfse (LDA effect Size) analysis for the microbiota in different groups of rats. Different colors indicate different groups. Note colored in a group color showed an important microbe biomarker in the group and the biomarker name is listed in the upper right corner. The yellow notes represent the biomarker which did not show any importance in groups. C, Relative abundance of the represented genus (Ruminococcaceae UCG-005, most significantly changed) in the colon microbiota of different groups. NC, non-diabetic control; DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW).

  • Figure 6

    (Color online) A and B, Global metabolic profiles represented by 3D partial least squares-discriminant analysis (PLS-DA). Venn diagram of significant metabolites (C) and metabolic pathway (D). E, ChemRICH set enrichment statistics plot. Each node reflected a significantly altered cluster of metabolites. Enrichment P-values were given by the Kolmogorov-Smirnov test. Node sizes represent the total number of metabolites in each cluster set. The node color scale shows the proportion of increased (red) or both increased and decreased metabolites (purple) in T2DM rats compared to NC rats. NC, non-diabetic control; DC, un-treated diabetic control; PC, positive control (metformin, 70 mg kg–1 BW); CP, non-diabetic+CP (300 mg kg–1 BW); CL, diabetic+CP (200 mg kg–1 BW); CM, diabetic+CP (300 mg kg–1 BW); CH, diabetic+CP (400 mg kg–1 BW).

  • Figure 7

    (Color online) A, Compound network related to the seven improved metabolic pathways by Cyclocarya paliurus polysaccharide. Red circles indicate the detected metabolites. Node sizes of red circles represent the fold change (L-kynurenine=1.1) of the metabolites in the DM group compared with the metabolites in polysaccharide treatment groups (using the average abundance of metabolites in CL, CM, and CH groups). The green outer rings represent significance while the blue outer rings represent no significance. B, Mechanism for Cyclocarya paliurus polysaccharide attenuating type 2 diabetes through microbiota and metabolites profiles.

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