Identification of the DPP-IV Inhibitory Peptides from Donkey Blood and Regulatory Effect on the Gut Microbiota of Type 2 Diabetic Mice

Abstract

After being treated with protease K, peptides extracted from donkey blood were separated, identified, and characterized. The results showed that Sephadex G-25 medium purified with MW < 3 kDa had the highest dipeptidyl peptidase IV (DPP-IV) inhibition capacity. Three-hundred-and-thirty-four peptides were identified with UPLC−MS/MS. Peptide Ranker and molecular docking analysis were used to screen active peptides, and 16 peptides were finalized out of the 334. The results showed that the lowest binding energy between P7(YPWTQ) and DPP-IV was −9.1, and the second-lowest binding energy between P1(VDPENFRLL) and DPP-IV was −8.7. The active peptides(MW < 3 kDa) could cause a reduction in the fasting blood glucose levels of type 2 diabetic mice, improve glucose tolerance, and facilitate healing of the damaged structure of diabetic murine liver and pancreas. Meanwhile, the peptides were found to ameliorate the diabetic murine intestinal micro-ecological environment to a certain extent.

Keywords: DPP-IV inhibitory activity; diabetes; hemoglobin; intestinal flora; isolation and purification; molecular docking.

Figure 1

Scanning diagram of the total wavelength for donkey hemoglobin.

Figure 2

Dipeptidyl peptidase IV (DPP-IV) inhibitory activity of each fraction. Different letters indicate significant differences (p < 0.05).

Figure 3

(A) Molecular docking diagram of VDPENFRLL and DPP-IV. (B) Molecular docking diagram of YPWTQ and DPP-IV.

Figure 4

(A) Liver histology (hematoxylin and eosin (H&E) stain) in mice (×400). (B) Pancreas histology (H&E stain) in mice (×400). CK: Blank control group; NC: Model control group; PC: Sitagliptin group; HEL: Active peptide low-dose group; HEM: Active peptide medium-dose group; HEH: Active peptide high-dose group.

Figure 5

Analysis of samples and diversity indices of mice in different treatment groups. (A) Sobs curve. (B) Shannon index curve. (C) Rank abundance.

Figure 6

(A) Shannon index. (B) Simpson index. (C) Ace index. (D) Chao 1 index. Different letters indicate significant differences (p < 0.05).

Figure 7

The effect of different treatments on the composition of mice gut microbes. Histogram of family-level communities.

Figure 8

(A) Hierarchical clustering. (B) Principal Coordinates Analysis (PCoA) of different samples.

Figure 9

(A) Kyoto Encyclopedia of Genes and Genomes (KEGG) compound classification statistics. (B) PLS−DA analysis of microbial metabolites in the feces of the mouse groups. (C) Variable importance in projection (VIP) analysis of fecal microbial metabolites in the NC and HE groups. CK: Blank control group; NC: Model control group; HE: Two mice were randomly selected from each of the HEH, HEM, and HEL groups to be mixed. Compared with the NC group, * p < 0.05, ** p < 0.01.

Figure 10

Experimental general mode diagram.