Reproductive inefficiency in cattle has major impacts on overall productivity of cattle operations, increasing cost of production, and impacting the sustainability of the cattle enterprise. Decreased reproductive success and associated disease states have been correlated with the presence of specific microbes and microbial community profiles, yet details of the relationship between microbial communities and host physiology are not well known. The present study profiles and compares the microbial communities in the bovine uterus and vagina using 16S rRNA sequencing of the V1–V3 hypervariable region at the time of artificial insemination. Significant differences (p < 0.05) between the vaginal and uterine communities were observed at the level of α-diversity metrics, including Chao1, Shannon’s Diversity Index, and observed OTU. Greater clustering of vaginal OTU was apparent in principal coordinate analysis compared to uterine OTU, despite greater diversity in the vaginal community in both weighted and unweighted UniFrac distance matrices (p < 0.05). There was a significantly greater relative abundance of unassigned taxa in the uterus (p = 0.008), otherwise there were few differences between the overall community profiles. Both vaginal and uterine communities were dominated by Firmicutes, although the relative abundance of rRNA sequences corresponding to species in this phylum was significantly (p = 0.007) lower in the uterine community. Additional differences were observed at the genus level, specifically in abundances within Clostridium (p = 0.009), Anaerofustis (p = 0.018), Atopobium (p = 0.035), Oscillospira (p = 0.035), 5-7N15 (p = 0.035), Mycoplasma (p = 0.035), Odoribacter (p = 0.042), and within the families Clostridiaceae (p = 0.006), Alcaligenaceae (p = 0.021), and Ruminococcaceae (p = 0.021). Overall, the comparison revealed differences and commonalities among bovine reproductive organs, which may be influenced by host physiology. The increased abundance of unassigned taxa found in the uterus may play a significant biological role in the reproductive status of the animal. The study represents an initial dataset for comparing bacterial communities prior to establishment of pregnancy.

The current study characterized the taxonomic composition of the uterine and vaginal bacterial communities during estrous synchronization up to timed artificial insemination (TAI). Postpartum beef cows (n = 68) were subjected to pre-synchronization step 21 d prior to TAI (day −21), followed by an industry standard 7 Day Co-Synch on day −9 and TAI on day 0. Uterine and vaginal flushes were collected on days −21, −9, and −2 of the protocol and pH was immediately recorded. Pregnancy was determined by transrectal ultrasound on day 30. Bacterial DNA was extracted and sequenced targeting the V1 to V3 hypervariable regions of the 16S rRNA bacterial gene. Results indicated 34 different phyla including 792 different genera present between the uterus and vagina. Many differences in the relative abundance of bacterial phyla and genera occurred between resulting pregnancy statuses and among protocol days (P < 0.05). At day −2, multiple genera were present in >1% abundance of nonpregnant cows but <1% abundance in pregnant cows (P < 0.05). Uterine pH increased in nonpregnant cows but decreased in pregnant cows (P > 0.05). Overall, our study indicates bacterial phyla and genera abundances shift over time and may potentially affect fertility by altering the reproductive tract environment.

The present study evaluated the bovine vaginal and uterine bacterial community diversity and its relationship to fertility. Postpartum beef cows (n = 68) were synchronized beginning on day −21 and ending with timed artificial insemination (TAI) on day 0. Pregnancy was diagnosed 30 d after TAI. Uterine and vaginal flushes were collected on day −21, −9, and −2 for bacterial DNA extraction to sequence the V1 to V3 hypervariable regions of the 16S rRNA gene. Results indicated a decrease in the number of bacterial species over time in the uterus of resulting pregnant and nonpregnant beef cows (P < 0.0001). Principal coordinate analyses (PCoA) depicted clustering of samples, indicating closely related bacterial communities, by day in the uterus and vagina (P < 0.0001). At day −2, uterine samples from nonpregnant and pregnant animals clustered separately (P < 0.0001), with nonpregnant animal samples clustering tightly together. Overall, the current study suggests the shift in the reproductive bacterial communities’ diversity and phylogenetic relationship leading up to the time of breeding may contribute to successful pregnancy establishment.

The beef cattle industry represents a significant portion of the USA's agricultural sect, with beef cattle accounting for the most red meat consumed in the USA. Feed represents the largest input cost in the beef industry, accounting for approximately 70% of total input cost. Given that, novel methods need to be employed to optimize feed efficiency in cattle to reduce monetary cost as well as environmental cost associated with livestock industries, such as methane production and nitrogen release into the environment. The rumen microbiome contributes to feed efficiency by breaking down low-quality feedstuffs into energy substrates that can subsequently be utilized by the host animal. Attempts to manipulate the rumen microbiome have been met with mixed success, though persistent changes have not yet been achieved beyond changing diet. Recent technological advances have made analyzing host-wide effects of the rumen microbiome possible, as well as provided finer resolution of those effects. This manuscript reviews contributing factors to the rumen microbiome establishment or re-establishment following rumen microbiome perturbation, as well as host-microbiome interactions that may be responsible for possible host specificity of the rumen microbiome. Understanding and accounting for the variety of factors contributing to rumen microbiome establishment or re-establishment in cattle will ultimately lead to identification of biomarkers of feed efficiency that will result in improved selection criteria, as well as aid to determine methods for persistent microbiome manipulation to optimize production phenotypes.

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