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. 2025 Jul 2;15(7):447.
doi: 10.3390/metabo15070447.

Multi-Omics Analysis of Gut Microbiota and Sperm Quality in Tibetan Breeding Boars

Mingxuan Zhao  1   2   3 , Mengjia Han  1   2   3 , Hongliang Zhang  1   2   3 , Xiangdong Wang  1   2   3 , Yikai Yin  1   2   3 , Jian Zhang  1   2   3 , Peng Shang  1   2   3
Affiliations

Multi-Omics Analysis of Gut Microbiota and Sperm Quality in Tibetan Breeding Boars

Mingxuan Zhao et al. Metabolites. .

Abstract

Background/objectives: Reproductive efficiency in breeding boars critically impacts swine industry productivity, with sperm quality being multifactorially regulated by gut microbiota. This study aimed to elucidate the microbiota-metabolite interactions underlying sperm quality differences in Tibetan boars.

Methods: Integrated 16S rRNA sequencing and untargeted metabolomics were performed on fecal and semen samples from eight healthy Tibetan boars (31-33 months old), stratified into low-semen (CJ) and high-semen utilization (HJ) groups. Analyses included sperm quality assessment, microbial profiling, and metabolic pathway enrichment.

Results: The HJ group exhibited significantly enhanced sperm motility and semen utilization rates (p < 0.05). Gut microbiota composition differed markedly, with Firmicutes and Proteobacteria enriched in HJ boars. Metabolomics identified key metabolites positively correlated with sperm quality (e.g., butyrate, phenyllactic acid), while lithocholic acid showed negative associations. KEGG analysis revealed predominant involvement in butanoate metabolism and bile acid biosynthesis. Core microbiota (e.g., Ruminococcus) modulated sperm quality through short-chain fatty acid networks and bile acid homeostasis.

Conclusions: Gut microbiota regulated the sperm microenvironment via a "metabolic-immune" dual pathway mediated by the gut-testis axis. These findings establish a theoretical basis for probiotic or metabolite-targeted strategies to improve boar reproductive performance.

Keywords: 16S rRNA; gut microbiota; gut–testis axis; metabolomics; sperm quality.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
Gut microbiota diversity and biomarker analysis in breeding boars with divergent semen quality (A) Venn diagram illustrating amplicon sequence variant (ASV) distribution between the high semen utilization group (HJ group) and low semen utilization group (CJ group); (B) Circos plot of core taxa (top 10 relative abundance at phylum to genus levels, ASV ≥ 2000) across groups; (C–F) Alpha diversity indices (Shannon, Simpson, observed OTUs) and beta diversity (weighted UniFrac PCoA).
Figure 2
Figure 2
Gut microbial composition and functional pathway divergence; (A) LEfSe analysis highlighting discriminant taxa (LDA score > 3.0); (B) Phylum-level abundance differences and microbial community separation (weighted UniFrac PCoA); (C) Sankey diagram mapping PICRUSt-predicted metabolic flux variations; (D,E) KEGG pathway enrichment (level 3) based on PICRUSt prediction for HJ and CJ groups.
Figure 3
Figure 3
Classification model analysis of high and low semen utilization groups based on untargeted metabolomics (A) PLS-DA score plot (positive ion mode); (B) PLS-DA score plot (negative ion mode); (C) OPLS-DA model (positive ion mode); (D) OPLS-DA model (negative ion mode); (E) Volcano plot of differential metabolites (positive ion mode); (F) Volcano plot of differential metabolites (negative ion mode).
Figure 4
Figure 4
Differential metabolites and metabolic pathway analysis between high and low semen utilization groups (A) Clustering heatmap of differential metabolites (positive ion mode); (B) Clustering heatmap of differential metabolites (negative ion mode); (C) KEGG pathway classification histogram; (D) KEGG enrichment circle plot; (E) KEGG enrichment bubble plot.
Figure 5
Figure 5
Correlation between differential metabolites and semen quality-associated microbiota (A) Microbial loading plot of differential metabolites associated with semen quality; (B) Correlation network of differential metabolites and semen quality-associated microbiota, note:red lines represent statistically significant correlations (p < 0.05).
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