Characterizing the Fermentation of Oat Grass (Avena sativa L.) in the Rumen: Integrating Degradation Kinetics, Ultrastructural Examination with Scanning Electron Microscopy, Surface Enzymatic Activity, and Microbial Community Analysis

Abstract

The objective of this study is to investigate the degradation characteristics of oat grass in the rumen of Mindong goats and changes in microbial community attached to the grass surface. Four healthy male goats, aged 14 months, with permanent rumen fistula, in eastern Fujian, were selected as experimental animals. The rumen degradation rate of oat grass was measured at 4, 12, 24, 36, 48, and 72 h using the nylon bag method. Surface physical structure changes in oat grass were observed using scanning electron microscopy (SEM), cellulase activity was measured, and bacterial composition was analyzed using high-throughput 16S rRNA gene sequencing technology. The findings of this study indicate that oat grass had effective degradation rates (ED) of 47.94%, 48.69%, 38.41%, and 30.24% for dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), and acidic detergent fiber (ADF), respectively. The SEM was used to investigate the degradation process of oat grass in the rumen. After 24 h, extensive degradation of non-lignified tissue was observed, resulting in the formation of cavities. At 36 h, significant shedding was observed, and by 72 h, only the epidermis and thick-walled tissue, which exhibited resistance to degradation, remained intact. Surface-attached microorganisms produced β-GC, EG, CBH, and NEX enzymes. The activity of these enzymes exhibited a significant increase between 4 and 12 h and showed a positive correlation with the degradation rate of nutrients. However, the extent of correlation varied. Prevotella and Treponema were identified as key genera involved in the degradation of roughage, with their abundance decreasing over time. Principle Coordinate Analysis (PCOA) revealed no significant differences in the rumen microbial structure across different time points. However, Non-Metric Multidimensional Scaling (NMDS) indicated a discernible diversity order among the samples. According to the Spearman correlation coefficient test, Ruminococcus, Fibrobacter, and Saccharoferments exhibited the closest relationship with nutrient degradation rate and surface enzyme activity, displaying a significant positive correlation. In summary, this study delineates a time-resolved correlative framework linking microbial succession to structural and enzymatic dynamics during oat grass degradation.

Keywords: Avena sativa L.; cellulase; electron microscopy scanning; rumen degradation rate; rumen microbiota.

Figure 1

Changes in the structure and tissue of oat grass under SEM: (A) 4 h; (B) 12 h; (C) 24 h; (D) 36 h; (E) 72 h. At each time point, pictures of oat structure under 100 μm, 50 μm, and 10 μm microscope scales are displayed.

Figure 2

Cellulase activity attached to the surface of oat during rumen degradation: (A) β-Glucosidase; (B) endo-1,4-β-D-glucanohydrolase; (C) exo-1,4-β-D-glucanase; (D) Neutral xylanase. Different lowercase letters in the same row indicate significant differences (p < 0.05).

Figure 3

OTU Venn diagram analysis.

Figure 4

Principal coordinate analysis (PCoA) and non-metric multidimensional analysis (NMDS) of rumen microbial community structure at different time points for oat based on unweighted unifrac distance: (A) PCoA; (B) NMDS.

Figure 5

Relative abundance of phylum-level microorganisms (%): (A) Phylum-level taxonomic relative abundance variation; (B) Changes in relative abundance at the phylum level. Different lowercase letters in the same row indicate significant differences (p < 0.05).

Figure 6

Relative abundance of genus-level microorganisms (%): (A) Genus-level taxonomic relative abundance variation; (B) Changes in relative abundance at the genus level. Different lowercase letters in the same row indicate significant differences (p < 0.05).

Figure 7

LEfSe analysis branch graph at different time points.

Figure 8

Analysis of the composite correlation plot of nutrient degradation rate and enzyme activity. Note: Arranged from right to left, these are box plots, correlation analysis data, density plots, and scatter plots, with histograms at the bottom. These visual representations depict the distribution and correlation of nutrient degradation rates and enzyme activity at 4, 12, 24, 36, and 72 h from various perspectives. The “corr” indicate the correlation coefficient (range from −1 to 1); “*” represents p < 0.05; “**” represents p < 0.01; and “***” represents p < 0.001.

Figure 9

The correlation between nutrient degradation rate, cellulase activity, and rumen bacteria. Blue represents negative correlation, while pink represents positive correlation: (A) 4 h; (B) 12 h; (C) 24 h; (D) 36 h; (E) 72 h; (F) 4–72 h.

Figure 10

The function of the rumen microbiota in experimental goat samples was predicted using PICRUSt2 software: (A) KEGG Top-level pathways; (B) KEGG Level 2 pathways; (C) KEGG Level 3 pathways; (D) KO-based K-means clustering heatmap. * indicates p < 0.05, ** indicates p < 0.01, *** indicates p < 0.001. For the classification cluster, n is the number, the ordinate indicates the normalized material content, and the best number of clusters is calculated according to the Calinski–Harabasz algorithm.

Figure 11

Network analysis of correlation between carbohydrate metabolism pathways and rumen flora. Note: The size and color depth of the circle (green to purple) indicate the extent of the associated object in the legend to the right. Purple and green nodes indicate centrality. Lines connected to the nodes indicate a significant correlation between the species, and the thickness of the lines indicates the strength of the correlation (|r| > 0.5, p < 0.05). Yellow and silver lines indicate positive and negative correlations, respectively.