Microbial contamination of bovine raw milk often occurs at the farm. To acquire a deeper knowledge of the microbiota of farm tank milk, we studied milk from 45 farms situated in 2 geographical areas in Norway. Each farm was visited on 3 different occasions, with at least 2 wk between visits. We combined both bacterial cell counts and a sequence variant inference method of amplicon-based high-throughput sequencing to achieve a high-resolution overview of the microbiota in each sample. Compositional variation of the farm milk microbiota was shown in relation to the 2 areas, between the farms and between the sampling times. Despite the near constant level of bacteria enumerated in milk from each individual farm, the dominant microbiota differed significantly between the samplings. The predominant microbiota was dominated by spoilage genera, such as Pseudomonas and Bacillus, as well as the dairy fermentation genus Lactococcus and mastitis-causing organisms (Streptococcus). Analysis of the identified sequence variants within these genera showed that the populations of Pseudomonas and Lactococcus in milk had similar composition between the farms, but that Bacillus and, in particular, Streptococcus populations changed between collection days from the same farm and between farms and geographical areas. Furthermore, the levels and composition of Bacillus and Paenibacillus were different between the 2 geographical areas. The results presented here provide new insight into the farm milk microbiota and show that this microbiota is a dynamic community highly subject to variation.

Classification of pathogenic Escherichia coli (E. coli) has traditionally relied on detecting specific virulence associated genes (VAGs) or combinations thereof. For E. coli isolated from faecal samples, the presence of specific genes associated with different intestinal pathogenic pathovars will determine their classification and further course of action. However, the E. coli genome is not a static entity, and hybrid strains are emerging that cross the pathovar definitions. Hybrid strains may show gene contents previously associated with several distinct pathovars making the correct diagnostic classification difficult. We extended the analysis of routinely submitted faecal isolates to include known virulence associated genes that are usually not examined in faecal isolates to detect the frequency of possible hybrid strains. From September 2012 to February 2013, 168 faecal isolates of E. coli routinely submitted to the Norwegian Institute of Public Health (NIPH) from clinical microbiological laboratories throughout Norway were analysed for 33 VAGs using multiplex-PCR, including factors associated with extraintestinal pathogenic E. coli (ExPEC) strains. The strains were further typed by Multiple Locus Variable-Number Tandem-Repeat Analysis (MLVA), and the phylogenetic grouping was determined. One isolate from the study was selected for whole genome sequencing (WGS) with a combination of Oxford Nanopore’s MinION and Illumina’s MiSeq. The analysis showed a surprisingly high number of strains carrying ExPEC associated VAGs and strains carrying a combination of both intestinal pathogenic E. coli (IPEC) and ExPEC VAGs. In particular, 93.5% (101/108) of isolates classified as belonging to an IPEC pathovar additionally carried ExPEC VAGs. WGS analysis of a selected hybrid strain revealed that it could, with present classification criteria, be classified as belonging to all of the Enteropathogenic Escherichia coli (EPEC), Uropathogenic Escherichia coli (UPEC), Neonatal meningitis Escherichia coli (NMEC) and Avian pathogenic Escherichia coli (APEC) pathovars. Hybrid ExPEC/IPEC E. coli strains were found at a very high frequency in faecal samples and were in fact the predominant species present. A sequenced hybrid isolate was confirmed to be a cross-pathovar strain possessing recognised hallmarks of several pathovars, and a genome heavily influenced by horizontal gene transfer.

The importance of the microbiome for bovine udder health is not well explored and most of the knowledge originates from research on mastitis. Better understanding of the microbial diversity inside the healthy udder of lactating cows might help to reduce mastitis, use of antibiotics and improve animal welfare. In this study, we investigated the microbial diversity of over 400 quarter milk samples from 60 cows sampled from two farms and on two different occasions during the same lactation period. Microbiota analysis was performed using amplicon sequencing of the 16S rRNA gene and over 1000 isolates were identified using MALDI-TOF MS. We detected a high abundance of two bacterial families, Corynebacteriaceae and Staphylococcaceae, which accounted for almost 50% of the udder microbiota of healthy cows and were detected in all the cow udders and in more than 98% of quarter milk samples. A strong negative correlation between these bacterial families was detected indicating a possible competition. The overall composition of the udder microbiota was highly diverse and significantly different between cows and between quarter milk samples from the same cow. Furthermore, we introduced a novel definition of a dysbiotic quarter at individual cow level, by analyzing the milk microbiota, and a high frequency of dysbiotic quarter samples were detected distributed among the farms and the samples. These results emphasize the importance of deepening the studies of the bovine udder microbiome to elucidate its role in udder health.

Introduction of microbial contaminations in the dairy value chain starts at the farm level and the initial microbial composition may severely affect the production of high-quality dairy products. Therefore, understanding the farm-to-farm variation and longitudinal shifts in the composition of the bulk tank milk microbiota is fundamental to increase the quality and reduce the spoilage and waste of milk and dairy products. In this study, we performed a double experiment to study long- and short-term longitudinal shifts in microbial composition using 16S rRNA gene amplicon sequencing. We analyzed milk from 37 farms, that had also been investigated two years earlier, to understand the stability and overall microbial changes over a longer time span. In addition, we sampled bulk tank milk from five farms every 1–2 weeks for up to 7 months to observe short-term changes in microbial composition. We demonstrated that a persistent and farm-specific microbiota is found in bulk tank milk and that changes in composition within the same farm are mostly driven by bacterial genera associated with mastitis (e.g., Staphylococcus and Streptococcus). On a long-term, we detected that major shift in milk microbiota were not correlated with farm settings, such as milking system, number of cows and quality of the milk but other factors, such as weather and feeding, may have had a greater impact on the main shifts in composition of the bulk tank milk microbiota. Our results provide new information regarding the ecology of raw milk microbiota at the farm level.