Studies on fatty acids and microbiota characterization of the gastrointestinal tract of Tianzhu white yaks

Abstract

Introduction: The gut microbiota significantly influences the host's production performance and health status, with different gastrointestinal tissues exhibiting functional diversity reflected in their microbial diversity.

Methods: In this study, five adult male Tianzhu white yaks (4.5 years old) were selected and fed under the same nutritional conditions. After the feeding experiment, the yaks were slaughtered, and chyme samples were collected from the rumen, abomasum, jejunum, and colon for 16S rRNA full-length sequencing and volatile fatty acid analysis.

Results: The results showed that the microbial composition and diversity of the rumen and abomasum were similar, with close genetic distances and functional projections. In contrast, the jejunum and colon had distinct microbial compositions and diversity compared to the rumen and abomasum. At the phylum level, the dominant phyla in the rumen, abomasum, and colon were Firmicutes and Bacteroidetes, while in the jejunum, the dominant phyla were Firmicutes and Proteobacteria. The abundance of Firmicutes differed significantly between the jejunum (87.24%) and the rumen (54.67%), abomasum (67.70%), and colon (65.77%). Similarly, Bacteroidetes showed significant differences between the jejunum (2.21%) and the rumen (36.54%), abomasum (23.81%), and colon (28.12%). At the genus level, Rikenellaceae_RC9_gut_group and Christensenellaceae_R-7_group were dominant in both the rumen and abomasum. In the jejunum, Romboutsia and Paeniclostridium were dominant, while Rikenellaceae_RC9_gut_group and UCG-005 were the dominant genera in the colon. At the species level, rumen_bacterium_g_Rikenellaceae_RC9_gut_group and rumen_bacterium_g_Christensenellaceae_R-7_group were dominant in both the rumen and abomasum, while Clostridium_sp._g_Romboutsia and bacterium_g_Paeniclostridium were unique to the jejunum. Ruminococcaceae_bacterium_g_UCG-005 and bacterium_g_Rikenellaceae_RC9_gut_group were unique to the colon. KEGG functional prediction of the microbiota indicated that the dominant functions in the rumen, abomasum, colon, and jejunum were amino acid metabolism, glycan biosynthesis and metabolism, carbohydrate metabolism, and membrane transport, respectively, reflecting the digestive functions of these organs. Volatile fatty acid analysis showed that the concentrations of acetic acid, propionic acid, and butyric acid in the rumen were significantly higher than those in the abomasum, jejunum, and colon (p < 0.05). Among these, the propionic acid concentration in the jejunum was significantly lower than in the abomasum and colon. Additionally, correlation analysis results indicated that acetic acid and butyric acid were significantly positively correlated with the ruminal bacterial community (p < 0.05). The total volatile fatty acid concentration was highest in the rumen, decreased to less than one-fifth of the rumen's total volatile fatty acid concentration in the abomasum and jejunum, and then reached a second peak in the colon.

Conclusion: This study explored the microbial composition and differential bacterial genera in the rumen and intestines of Tianzhu white yak, comparing the differences in volatile fatty acid levels and microbial composition and function across different regions. This is important for understanding their gastrointestinal microbiota's spatial heterogeneity.

Keywords: Tianzhu white yak; function; gastrointestinal; microbiota; volatile fatty acids.

Figure 1

Fatty acid analysis of the gastrointestinal tract of yak. (A–G) Show the difference between acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid and total acid contents among gastrointestinal groups using the single-factor ANOVA. In the figure, different letters a, b, and c represent significant differences (p < 0.05), while the same letters or those containing the same letters are not significant (p < 0.05).

Figure 2

(A) Venn diagram analysis of species based on OTU level. (B) Rank-abundance curves can be used to explain two aspects of diversity, namely, species richness and community evenness. In the horizontal direction, species richness is reflected by the curve’s width. The larger the range of the curve on the horizontal axis, the higher the species richness. The shape of the curve (flatness) reflects the uniformity of the community in the sample, and the gentler the curve, the more evenly distributed the species. (C) Pan/Core species analysis is used to describe changes in total species and core species as the sample size increases and is widely used to determine whether the sample size is adequate.

Figure 3

Composition and proportion of microorganisms. (A) Principal coordinate analysis (PCoA) based on all samples. (B) ANOSIM. (C) Phylum-level microbial composition at each site. (D) Generic microbial composition of each site. (E) Species-level microbial composition at each site.

Figure 4

Linear discriminant analysis (LDA) effect size (LEfSe) analysis of gastrointestinal segments in Tianzhu white yak. LEfSe analysis histogram of each gastrointestinal segment (A). The ordinate is the significantly different taxa between the groups, and the abscess is a bar chart showing the LDA logarithmic fraction value for each taxon. The longer the length, the more significant the difference in taxa. (B) LEfSe analysis of each segment of the gastrointestinal tract. Node size corresponds to the average relative abundance of taxa, and hollow nodes represent taxa that do not differ significantly between taxa. These letters identify taxa names that vary widely between groups.

Figure 5

Enrichment analysis of KEGG metabolic pathways. (A–F) Show the differential analyses of metabolic pathways between the following pairs: rumen and abomasum, rumen and jejunum, rumen and colon, abomasum and jejunum, and jejunum and colon, respectively.

Figure 6

Correlation analysis of gastrointestinal microorganisms and VFAs in yaks. The Mantel-test network heatmap (A) shows the correlation between gastrointestinal fermentation parameters and microbial community structure. The lines in the figure represent the correlation between community and environmental factors, and the heatmap represents the correlation between environmental factors. Line thickness indicates the correlation between community and environmental factors is drawn with Mantel’r (absolute value of r). The relationship is categorized as Positive and Negative, indicating positive and negative correlations between community and environmental factors. Different colors in the heatmap represent positive and negative correlations, color depth represents the magnitude of positive and negative correlations, and asterisks in color blocks represent significance, *0.01 < p ≤ 0.05, **0.001 < p ≤ 0.01, and ***p ≤ 0.001. Spearman’s correlation heatmap (B) shows the correlation between species and environmental factors (X and Y axes are environmental factors and species, respectively, and R-and p-values were obtained by calculation. The R values are shown in different colors in the chart. If the p-value is less than 0.05, it is marked with a *. The legend on the right is the color interval of the different R values. **0.001, *0.01 < 0.05, or less p < p 0.01, or less ***p < 0.001 or less).

Figure 7

Overview of the gastrointestinal digestive process in Tianzhu white yak.