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. 2024 Oct 9:15:1471732.
doi: 10.3389/fmicb.2024.1471732. eCollection 2024.

Unique rumen micromorphology and microbiota-metabolite interactions: features and strategies for Tibetan sheep adaptation to the plateau

Qianling Chen  1 , Yuzhu Sha  1 , Xiu Liu  1 , Yanyu He  2 , Xiaowei Chen  1 , Wenxin Yang  1 , Min Gao  1 , Wei Huang  1 , Jiqing Wang  1 , Jianwen He  3 , Lei Wang  1   4
Affiliations

Unique rumen micromorphology and microbiota-metabolite interactions: features and strategies for Tibetan sheep adaptation to the plateau

Qianling Chen et al. Front Microbiol. .

Abstract

The rumen microbiota-a symbiont to its host and consists of critical functional substances-plays a vital role in the animal body and represents a new perspective in the study of adaptive evolution in animals. This study used Slide Viewer slicing analysis system, gas chromatography, RT-qPCR and other technologies, as well as 16S and metabolomics determination methods, to measure and analyze the microstructure of rumen epithelium, rumen fermentation parameters, rumen transport genes, rumen microbiota and metabolites in Tibetan sheep and Hu sheep. The results indicate that the rumen nipple height and cuticle thickness of Tibetan sheep are significantly greater than those of Hu sheep (p < 0.01) and that the digestion and absorption of forage are greater. The levels of carbohydrate metabolism, lipid metabolism, and protein turnover were increased in Tibetan sheep, which enabled them to ferment efficiently, utilize forage, and absorb metabolic volatile fatty acids (VFAs). Tibetan sheep rumen metabolites are related to immune function and energy metabolism, which regulate rumen growth and development and gastrointestinal homeostasis. Thus, compared with Hu sheep, Tibetan sheep have more rumen papilla and cuticle corneum, and the synergistic effect of the microbiota and its metabolites is a characteristic and strategy for adapting to high-altitude environments.

Keywords: 16S rRNA; Hu sheep; Tibetan sheep; VFAs; metabolomics; transporter genes.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Morphology of rumen epithelial tissue of Tibetan sheep and Hu sheep. (A–C) The morphology of rumen epithelial tissue of Tibetan sheep at 1×, 10×, and 2× magnifications, respectively; (D–F) The morphology of rumen epithelial tissue of Hu sheep at 1×, 10×, and 2× magnifications, respectively. a: Cuticle; b: Granular layer; c: Spinous layer; d: Basal layer.
Figure 2
Figure 2
Analysis of microbial diversity in Tibetan sheep and Hu sheep. (A) Scatter plot of principal coordinates components (PCoA)-score showing similarity of the microbiological composition of Tibetan sheep and Hu sheep based on UniFrac distance, principal coordinates (PCs) 1 and 2 explained 14.51 and 12.37% of the variance, respectively. (B) OTU Venn diagram. (C) Sample dilution curve. (D–G) Microbial diversity indicators—(D): ACE index; (E): Chao1 index; (F): Shannon index; and (G): Simpson index.
Figure 3
Figure 3
Analysis of the microbiological composition of Tibetan sheep and Hu sheep. (A,C) Microbial composition at the level of phylum and genus. (B,D) Analysis of species differences at phylum and genus level.
Figure 4
Figure 4
Intestinal microbial function analysis of Tibetan sheep and Hu sheep. (A) Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analysis. (B) Clusters of Orthologous Groups of proteins (COG) functional analysis.
Figure 5
Figure 5
Quality control diagram of rumen microbial metabolome data of Tibetan sheep and Hu sheep. (A) Scatter plot of principal component analysis (PCA)-score showing the similarity of the rumen metabolites of Tibetan sheep and Hu sheep based on UniFrac distance, principal components (PCs) 1 and 2 explained 43.59 and 24.61% of the variance, respectively. (B) Orthogonal projections to late structures discriminant analysis (OPLS-DA) based on operational taxonomic units (OTUs) of rumen metabolites in Hu sheep and Tibetan sheep. (C) Volcanic maps of differential metabolites in Tibetan sheep and Hu sheep. (D) Column chart of positive ion difference multiples.
Figure 6
Figure 6
The Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analysis diagram of differential metabolites in rumen microbiomes of Tibetan sheep and Hu sheep. (A) Differential metabolite KEGG pathway classification annotation. (B) Differential metabolite differential abundance score diagram.
Figure 7
Figure 7
Rumen volatile fatty acids (VFAs) transport gene expression results of Tibetan sheep and Hu sheep. **Indicates highly significant difference (p < 0.01).
Figure 8
Figure 8
Correlation analysis of rumen microbiomes and metabolites in Tibetan sheep and Hu sheep. (A) Microbiomes and metabolites correlation heat map. (B) Microbiomes and metabolites correlation chord diagram. *p < 0.05, **p < 0.01, ***p < 0.001.
Figure 9
Figure 9
Correlation heat map between Tibetan sheep and Hu sheep. (A) Heat map of correlation between horizontal rumen microbiomes and VFAs and transport genes. (B) Heat map of morphological correlation between rumen microbiomes and rumen epithelium. (C) Heat map of correlation between rumen VFAs and transport genes.
Figure 10
Figure 10
The results of WGCNA. (A) Cluster dendrogram of rumen metabolites in Tibetan sheep and Hu sheep. Each branch in the figure represents one metabolite, and each color represents one coexpression module. (B) Correlation between the rumen metabolite modules, transport genes and rumen epithelial morphology in Tibetan sheep and Hu sheep.
Figure 11
Figure 11
Modeling of rumen microorganisms and their fermentative metabolism in Tibetan sheep and Hu sheep.
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Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was funded by the National Natural Science Foundation of China (32260820), the Discipline Team Project of Gansu Agricultural University (GAU-XKTD-2022-21), the Gansu Agricultural University Youth Mentor Support Fund project (GAU-QDFC-2022-06), the Gansu Province Science and Technology Plan Project (Key R&D Program) (23YFFA0027), and the Gansu Province Higher Education Innovation Fund Project (2021A-441).

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