Association between semen microbiome disorder and sperm DNA damage

Abstract

DNA fragmentation index (DFI), a new biomarker to diagnose male infertility, is closely associated with poor reproductive outcomes. Previous research reported that seminal microbiome correlated with sperm DNA integrity, suggesting that the microbiome may be one of the causes of DNA damage in sperm. However, it has not been elucidated how the microbiota exerts their effects. Here, we used a combination of 16S rRNA sequencing and untargeted metabolomics techniques to investigate the role of microbiota in high sperm DNA fragmentation index (HDFI). We report that increased specific microbial profiles contribute to high sperm DNA fragmentation, thus implicating the seminal microbiome as a new therapeutic target for HDFI patients. Additionally, we found that the amount of Lactobacillus species was altered: Lactobacillus iners was enriched in HDFI patients, shedding light on the potential influence of L. iners on male reproductive health. Finally, we also identified enrichment of the acetyl-CoA fermentation to butanoate II and purine nucleobase degradation I in the high sperm DNA fragmentation samples, suggesting that butanoate may be the target metabolite of sperm DNA damage. These findings provide valuable insights into the complex interplay between microbiota and sperm quality in HDFI patients, laying the foundation for further research and potential clinical interventions.IMPORTANCEThe DNA fragmentation index (DFI) is a measure of sperm DNA fragmentation. Because high sperm DNA fragmentation index (HDFI) has been strongly associated with adverse reproductive outcomes, this has been linked to the seminal microbiome. Because the number of current treatments for HDFI is limited and most of them have no clear efficacy, it is critical to understand how semen microbiome exerts their effects on sperm DNA. Here, we evaluated the semen microbiome and its metabolites in patients with high and low sperm DNA fragmentation. We found that increased specific microbial profiles contribute to high sperm DNA fragmentation. In particular, Lactobacillus iners was uniquely correlated with high sperm DNA fragmentation. Additionally, butanoate may be the target metabolite produced by the microbiome to damage sperm DNA. Our findings support the interaction between semen microbiome and sperm DNA damage and suggest that seminal microbiome should be a new therapeutic target for HDFI patients.

Keywords: 16S; RNA; metabolomics; microbiota; ribosomal.

Fig 1

Participants enrolled in the study.

Fig 2

Overview of cross-incubation and composition of the seminal microbiota. (A) The experimental workflow for cross-incubation. (B) Boxplots illustrating the level of DFI after cross-incubation with seminal plasma from HDFI or LDFI groups. (C) Boxplots comparing the Shannon index α-diversity of microbial communities in HDFI and LDFI groups. (D) Principal-component analysis plots of β-diversity in the two groups. Stacked plot of genus composition of HDFI and LDFI groups at the genus level (E) and species level (F).

Fig 3

Bioinformatic analysis of 16S rRNA gene sequencing data. (A) Linear discrimination analysis (LDA) effect size (LEfSe) analysis identified the microbes whose abundances significantly differed between the HDFI and LDFI groups. (B) Model candidates for disease discrimination were established using random forest model analysis. (C) Biplot of redundancy analysis (RDA) of the microbiota composition responding to the level of DFI. (D) Pie chart showing distribution proportions of different Lactobacillus species.

Fig 4

Functional alterations of the microbiota. Difference analyses of KEGG orthology (A–E) and metabolic pathways from all domains of life (metacyc) (F).

Fig 5

Metabolite composition and KEGG analysis. (A) Compositional patterns of metabolites in HDFI and HDFI groups. (B) Volcano plot showing differential metabolites between HDFI and HDFI groups. (C) Pie chart showing the percentage of the types of differential metabolites. KEGG analysis of upregulated (D) and downregulated differential metabolites (E).

Fig 6

The co-occurrence network of differential metabolites and microbiota.