Core Microbiome of Slovak Holstein Friesian Breeding Bulls’ Semen

SIMPLE SUMMARY: The aim of this study was to characterize the bacterial profile of semen collected from Holstein Friesian breeding bulls via a high-throughput sequencing approach for a 16S rRNA gene variability analysis. A total of 55 fresh semen samples of sexually mature breeding bulls were used in the study. They were gathered from Holstein Friesian breeding bulls at Slovak Biological Services in Nitra, Slovak Republic. To amplify the V4 region of the 16S rRNA bacterial gene, universal primers 515F and 806R enhanced by a 6 bp barcode identification sequence were used. The 16S rRNA high-throughput sequencing strategy was used. Two microbial clusters were identified among the analyzed samples—the first cluster was based on Actinobacteria and Firmicutes, while the second cluster contained a high prevalence of Fusobacteria. ABSTRACT: Bacterial contamination of semen is an important factor connected to the health status of bulls that may significantly affect semen quality for artificial insemination. Moreover, some important bovine diseases may be transmitted through semen. Up to now, only a very limited number of complex studies describing the semen microbiome of bulls have been published, as many bacteria are hard to cultivate using traditional techniques. The 16S rRNA high-throughput sequencing strategy allows for the reliable identification of bacterial profiles of bovine semen together with the detection of noncultivable bacterial species. Fresh samples from Holstein Friesian breeding bulls (n = 55) were examined for the natural variability in the present bacteria. Semen doses were selected randomly from Slovak Biological Services in Nitra, Slovak Republic. The most predominant phyla within the whole dataset were Firmicutes (31%), Proteobacteria (22%), Fusobacteria (18%), Actinobacteria (13%) and Bacteroidetes (12%). Samples of semen were divided into two separate clusters according to their microbiome compositions using a cording partition around a medoids analysis. Microbiomes of the first cluster (CL1) of samples (n = 20) were based on Actinobacteria (CL1 average = 25%; CL = 28%) and Firmicutes (CL1 = 38%; CL2 = 27%), while the second cluster (CL2; n = 35) contained samples characterized by a high prevalence of Fusobacteria (CL1 = 4%; CL2 = 26%). Some important indicator microbial groups were differentially distributed between the clusters.