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Vaginal bacterial community composition and concentrations of estradiol at the time of artificial insemination in Brangus heifers.

ABSTRACT: The knowledge surrounding the bovine vaginal microbiota and its implications on fertility and reproductive traits remains incomplete. The objective of the current study was to characterize the bovine vaginal bacterial community and estradiol concentrations at the time of artificial insemination (AI). Brangus heifers (n = 78) underwent a 7-d Co-Synch + controlled internal drug release estrus synchronization protocol. At AI, a double-guarded uterine culture swab was used to sample the anterior vaginal tract. Immediately after swabbing the vaginal tract, blood samples were collected by coccygeal venipuncture to determine concentrations of estradiol. Heifers were retrospectively classified as pregnant (n = 29) vs. nonpregnant (n = 49) between 41 and 57 d post-AI. Additionally, heifers were classified into low (1.1 to 2.5 pg/mL; n = 21), medium (2.6 to 6.7 pg/mL; n = 30), and high (7.2 to 17.6 pg/mL; n = 27) concentration of estradiol. The vaginal bacterial community composition was determined through sequencing of the V4 region from the 16S rRNA gene using the Illumina Miseq platform. Alpha diversity was compared via ANOVA and beta diversity was compared via PERMANOVA. There were no differences in the Shannon diversity index (alpha diversity; P = 0.336) or Bray-Curtis dissimilarity (beta diversity; P = 0.744) of pregnant vs. nonpregnant heifers. Overall, bacterial community composition in heifers with high, medium, or low concentrations of estradiol did not differ (P = 0.512). While no overall compositional differences were observed, species-level differences were present within pregnancy status and estradiol concentration groups. The implications of these species-level differences are unknown, but these differences could alter the vaginal environment thereby influencing fertility and vaginal health. Therefore, species-level changes could provide better insight rather than overall microbial composition in relation to an animal's reproductive health.

SUBMITTER: Messman RD

PROVIDER: S-EPMC7281872 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Infertility is a longstanding limitation in livestock production with important economic impact for the cattle industry. Female reproductive traits are polygenic and lowly heritable in nature, thus selection for fertility is challenging. Beef cattle operations leverage estrous synchronization in combination with artificial insemination (AI) to breed heifers and benefit from an early and uniform calving season. A couple of weeks following AI, heifers are exposed to bulls for an opportunity to become pregnant by natural breeding (NB), but they may also not become pregnant during this time period. Focusing on beef heifers, in their first breeding season, we hypothesized that: a- at the time of AI, the transcriptome of peripheral white blood cells (PWBC) differs between heifers that become pregnant to AI and heifers that become pregnant late in the breeding season by NB or do not become pregnant during the breeding season; and b- the ratio of transcript abundance between genes in PWBC classifies heifers according to pregnancy by AI, NB, or failure to become pregnant.We generated RNA-sequencing data from 23 heifers from two locations (A: six AI-pregnant and five NB-pregnant; and B: six AI-pregnant and six non-pregnant). After filtering out lowly expressed genes, we quantified transcript abundance for 12,538 genes. The comparison of gene expression levels between AI-pregnant and NB-pregnant heifers yielded 18 differentially expressed genes (DEGs) (ADAM20, ALDH5A1, ANG, BOLA-DQB, DMBT1, FCER1A, GSTM3, KIR3DL1, LOC107131247, LOC618633, LYZ, MNS1, P2RY12, PPP1R1B, SIGLEC14, TPPP, TTLL1, UGT8, eFDR?0.02). The comparison of gene expression levels between AI-pregnant and non-pregnant heifers yielded six DEGs (ALAS2, CNKSR3, LOC522763, SAXO2, TAC3, TFF2, eFDR?0.05). We calculated the ratio of expression levels between all gene pairs and assessed their potential to classify samples according to experimental groups. Considering all samples, relative expression from two gene pairs correctly classified 10 out of 12 AI-pregnant heifers (P?=?0.0028) separately from the other 11 heifers (NB-pregnant, or non-pregnant).The transcriptome profile in PWBC, at the time of AI, is associated with the fertility potential of beef heifers. Transcript levels of specific genes may be further explored as potential classifiers, and thus selection tools, of heifer fertility.

Project description:Background: Infertility is a longstanding limitation in livestock production with important economic impact for the cattle industry. Female reproductive traits are polygenic and lowly heritable in nature, thus selection for fertility is challenging. Beef cattle operations leverage estrous synchronization in combination with artificial insemination (AI) to breed heifers and benefit from an early and uniform calving season. A couple of weeks following AI, heifers are exposed to bulls for an opportunity to become pregnant by natural breeding (NB), but they may also not become pregnant during this time period. Focusing on beef heifers, in their first breeding season, we hypothesized that: a- at the time of AI, the transcriptome of peripheral white blood cells (PWBC) differs between heifers that become pregnant to AI and heifers that become pregnant late in the breeding season by NB or do not become pregnant during the breeding season; and b- the ratio of transcript abundance between genes in PWBC classifies heifers according to pregnancy by AI, NB, or failure to become pregnant. Results: We generated RNA-sequencing data from 23 heifers from two locations (A: six AI-pregnant and five NB-pregnant; and B: six AI-pregnant and six non-pregnant). After filtering out lowly expressed genes, we quantified transcript abundance for 12,538 genes. The comparison of gene expression levels between AI-pregnant and NB-pregnant heifers yielded 18 differentially expressed genes (DEGs) (ADAM20, ALDH5A1, ANG, BOLA-DQB, DMBT1, FCER1A, GSTM3, KIR3DL1, LOC107131247, LOC618633, LYZ, MNS1, P2RY12, PPP1R1B, SIGLEC14, TPPP, TTLL1, UGT8, eFDR≤0.02). The comparison of gene expression levels between AI-pregnant and non-pregnant heifers yielded six DEGs (ALAS2, CNKSR3, LOC522763, SAXO2, TAC3, TFF2, eFDR≤0.05). We calculated the ratio of expression levels between all gene pairs and assessed their potential to classify samples according to experimental groups. Considering all samples, relative expression from two gene pairs correctly classified 10 out of 12 AI-pregnant heifers (P=0.0028) separately from the other 11 heifers (NB-pregnant, or non-pregnant). Conclusion: The transcriptome profile in PWBC, at the time of AI, is associated with the fertility potential of beef heifers. Transcript levels of specific genes may be further explored as potential classifiers, and thus selection tools, of heifer fertility.

Project description:Vaginal washing is a common practice associated with adverse outcomes including bacterial vaginosis (BV) and HIV infection. Prior studies have not examined the associations between vaginal washing and individual vaginal bacteria, or whether these associations are independent of the effect of vaginal washing on BV. The purpose of this study was to characterize the association between vaginal washing and the presence and concentrations of vaginal bacteria associated with optimal and sub-optimal vaginal states. The analysis utilized data from participants in the placebo arm of the Preventing Vaginal Infections trial, which enrolled HIV-uninfected women from the United States and Kenya. Detection of bacterial taxa associated with BV was compared between visits with versus without reported vaginal washing. The effect of vaginal washing on a number of vaginal bacteria differed substantially (p<0.05) between the US and Kenya, so results were stratified by country. In US women, vaginal washing was associated with a significantly higher likelihood of detection of BV associated bacterium 1 (BVAB1) (relative risk [RR] 1.55, 95% confidence interval [CI] 1.15-2.09, p = 0.004), BVAB2 (RR 1.99, 95%CI 1.46-2.71, p<0.001), Mageeibacillus indolicus (RR 2.08, 95%CI 1.46-2.96, p<0.001), Atopobium vaginae (RR 1.34, 95%CI 1.13-1.59, p = 0.001), Leptotrichia/Sneathia species (RR 1.66, 95% CI 1.33-2.09, p<0.001), Megasphaera species (RR 1.78, 95%CI 1.34-2.37, p<0.001) and Gardnerella vaginalis (RR 1.08, 95%CI 1.01-1.16, p = 0.02). No significant association between vaginal washing and bacterial detection was found in Kenyan women. Adjustment for bacterial vaginosis diagnosed by Gram stain did not alter these results. This study provides evidence that the association between vaginal washing and detection of individual bacterial taxa can vary regionally. For some vaginal bacteria, the association with vaginal washing may be independent of the effect on Gram stain detection of BV. Larger prospective studies in diverse geographic settings should explore whether eliminating vaginal washing impacts the presence and concentrations of key vaginal bacteria.

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Vaginal bacterial community composition and concentrations of estradiol at the time of artificial insemination in Brangus heifers.

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