{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T15:39:01Z","timestamp":1785771541441,"version":"3.56.0"},"reference-count":65,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>The vaginal microbiota plays a key role in animals\u2019 health. Understanding its diversity and composition and associated changes occurring through the reproductive cycle represents valuable knowledge to disclose the mechanisms leading to dysbiosis and eventually to infection. Even if the human vaginal microbiota has been thoroughly studied, scarce research has been conducted on the vaginal microbiota of livestock. In this study, 16S rRNA gene-based sequencing was performed on vaginal samples of ten nulliparous ewes at three different sampling points: before the estrus synchronization protocol (T0), at the time of estrus before mating (Testrus), and the day of the pregnancy diagnosis (Tpreg). Preputial samples from the three males collected pre and post-mating were also analyzed. Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria were the most abundant phyla in vaginal samples. The most abundant genera were <jats:italic>Porphyromonas<\/jats:italic>, <jats:italic>Anaerococcus<\/jats:italic>, and <jats:italic>Peptinophilius<\/jats:italic>. Vaginal microbiota biodiversity decreased during pregnancy. Tenericutes (<jats:italic>Ureaplasma<\/jats:italic> spp.) increased significantly at Tpreg in both pregnant and non-pregnant ewes. Differences were observed between pregnant and non-pregnant ewes at Tpreg where pregnant ewes had a significantly higher abundance of <jats:italic>Actinobacillus<\/jats:italic> spp. and <jats:italic>Ureaplasma<\/jats:italic> spp. Ewes that were diagnosed with pregnancy at Tpreg showed a decreased abundance of gram-negative bacteria such as Bacteroidales, Campylobacterales, and Enterobacteriales. In addition, a significant decrease in the relative abundances of genera within Firmicutes, such as <jats:italic>Alloicoccus<\/jats:italic> (Lactobacillales), <jats:italic>Atopostipes<\/jats:italic> (Lactobacillales), and an uncultured bacteria W5053 from Family XI (Firmicutes, Clostridiales) was observed in non-pregnant ewes at Tpreg. The four most abundant phyla in the rams\u2019 prepuce were the same as in the ewes\u2019 vagina. The most abundant genus was <jats:italic>Corynebacterium<\/jats:italic>. No major differences were observed in the ram\u2019s preputial microbiota between pre and post-mating samples. Nevertheless, the differences in the taxonomic composition of ewes\u2019 vaginal microbiota between Testrus and Tpreg could be explained by the exposure to the preputial microbiota. This study offers new insights into the effects of several key steps of the ewe\u2019s reproductive cycle such as estrus-synchronization protocol, mating, and pregnancy on ovine vaginal microbiota. The knowledge of the microbiota dynamics during the reproductive cycle can help improve the reproductive outcomes of dams by identifying biomarkers and putative probiotics.<\/jats:p>","DOI":"10.3389\/fmicb.2023.1224910","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T04:40:50Z","timestamp":1704948050000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Description of the vaginal microbiota in nulliparous ewes during natural mating and pregnancy: preliminary signs of the male preputial microbiota modulation"],"prefix":"10.3389","volume":"14","author":[{"given":"Marta","family":"Barba","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marion","family":"Toquet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Empar","family":"Garc\u00eda-Rosell\u00f3","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jes\u00fas","family":"Gomis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan J.","family":"Quereda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pedro","family":"Gonz\u00e1lez-Torres","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bel\u00e9n","family":"Carbonetto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00c1ngel","family":"G\u00f3mez-Mart\u00edn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e14","DOI":"10.3389\/fninf.2014.00014","article-title":"Machine learning for neuroimaging with scikit-learn","volume":"8","author":"Abraham","year":"2014","journal-title":"Front. 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