Effects of concentrate feeding sequence on VFA production, and cecal microbiota of Dezhou donkeys by metagenomic technology

Abstract

Microorganisms residing in the cecum of donkeys are crucial for physiological processes, nutrient metabolism, and immune function. Feeding methods can affect the dynamic balance of animal gut microbiota, thereby affecting indicators such as volatile fatty acids. This study explores suitable feeding methods to promote actual production by changing the feeding order of concentrate. Fifteen Dezhou donkeys with similar age and weight profiles were randomly divided into three groups with the concentrate feeding sequence: fiber-to-concentrate (FC), concentrate-to-fiber (CF), and total mixed ration (TMR). The experiment spanned a duration of 82 days. The analyses conducted were primarily aimed at determining the effects of feeding on gut microbes, primarily using metagenomic sequencing techniques. The experimental findings revealed that the levels of valeric acid were notably higher in the CF and TMR groups compared to the FC group (p < 0.05). These results suggest that the feeding sequence exerts a certain impact on the microbial composition within the cecum of Dezhou donkeys. At the phylum level, the predominant microbiota consisted of Firmicutes and Bacteroidetes, with the CF group displaying a higher relative abundance of Firmicutes compared to both the FC and TMR groups. At the genus level, Prevotella, Bacteroides, and Fibrobacter were the dominant bacterial genera identified in cecum. The functional gene annotation analysis indicated a significantly lower abundance of lacZ (K01190), Por/nifJ (K03737), and ppdK (K01006) genes in CF group relative to the FC and TMR groups (p < 0.05), highlighting their roles in galactose metabolism and glycolysis, respectively. Moreover, the CF group exhibited a higher concentration of antibiotic resistance genes (tetO and tet44) in the gut microbiota compared to the TMR and FC groups (p < 0.05), underscoring the presence of numerous antibiotic resistance genes within the phyla Bacteroidetes, Firmicutes, and Proteobacteria. In conclusion, different precision feed sequences significantly impact the levels of volatile fatty acids in Dezhou fattening donkeys, modify the composition and functional genes of the cecal microbiota, and elucidate the microbial mechanisms influenced by the feeding sequence on the growth and metabolism. These insights are anticipated to provide a foundation for the rational design of precision feed sequences in practical agricultural settings.

Keywords: Cecal microbiota; Dezhou donkeys; VFA; concentrate feeding sequence; metagenomic technology.

Figure 1

Experimental flow chart.

Figure 2

Information analysis flow chart.

Figure 3

(A) Statistical diagram of length distribution of gene catalog. (B) Gene number Venn analysis graph. (C) Core gene dilution curve. (D) Pan gene dilution curve.

Figure 4

NMDS analysis at gate level.

Figure 5

(A) Statistics of the number of unigenes annotations in KEGG. (B) KEGG’s gate level-based PCA results display chart for species. (C) KEGG’s level 1 function annotation relative abundance bar chart. (D) KEGG’s KO functional abundance relative abundance column chart.

Figure 6

(A) Statistics of the number of Unigenes annotations in CAZy. (B) Display of PCA results for CAZy. (C) CAZy’s level 1 function annotation relative abundance bar chart. (D) Functional abundance clustering heatmap of CAZy.

Figure 7

(A) Abundance bar chart of different AROs in each group. (B) Overview of antibiotic resistance genes.

Figure 8

Analysis circle of resistance gene species attribution. (A) Analysis circle of CF resistance gene species attribution. (B) TMR resistance gene species attribution analysis circle. (C) Circle diagram of FC resistance gene species attribution analysis.