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Metagenomics Reveals Specific Microbial Features in Males with Semen Alterations.

Iolanda VenerusoFederica CariatiCarlo AlviggiLucio PastoreTomaiuolo RossellaValeria DArgenio
Published in: Genes (2023)
Infertility incidence is rising worldwide, with male infertility accounting for about 50% of cases. To date, several factors have been associated with male infertility; in particular, it has been suggested that semen microbiota may play a role. Here, we report the NGS-based analyses of 20 semen samples collected from men with (Case) and without (Control) semen alterations. Genomic DNA was extracted from each collected sample, and a specific PCR was carried out to amplify the V4-V6 regions of the 16S rRNA. Sequence reactions were carried out on the MiSeq and analyzed by specific bioinformatic tools. We found a reduced richness and evenness in the Case versus the Control group. Moreover, specific genera, the Mannheimia , the Escherichia_Shigella, and the Varibaculum, were significantly increased in the Case compared to the Control group. Finally, we highlighted a correlation between the microbial profile and semen hyperviscosity. Even if further studies are required on larger groups of subjects to confirm these findings and explore mechanistic hypotheses, our results confirm the correlation between semen features and seminal microbiota. These data, in turn, may open the way to the possible use of semen microbiota as an attractive target for developing novel strategies for infertility management.
Keyphrases
  • polycystic ovary syndrome
  • microbial community
  • machine learning
  • type diabetes
  • metabolic syndrome
  • gene expression
  • single molecule
  • copy number
  • deep learning
  • nucleic acid
  • fluorescent probe