Seasonal dynamics of bulk milk somatic cell count in grazing Norwegian dairy goats.

Somatic cell count (SCC) is a widely used indicator of milk quality in the dairy industry. It is a relatively good indicator of udder health in dairy cows, but strongly confounded by non-infection factors, including season, in dairy goats. This study's objectives were to estimate the variation in SCC explained by season and stage of lactation. We also investigated associations between SCC and other milk quality parameters routinely measured, including total bacterial count, fat, protein, and lactose content, in different seasons and stages of lactation. In this observational study, we included results from the routine analyses of bulk milk samples (n = 5,180) collected every third day in 88 Norwegian goat herds through one year. Herd information was collected via a questionnaire and from the dairy herd recording system. The herds had a notable increase in bulk SCC associated with the pasture season. The median bulk SCC was 470,000 cells/mL in deliveries from the indoor spring period and 1,100,000 cells/mL in the pasture season. During the indoor fall season, when most goat herds are in late lactation, the median SCC was 940,000 cells/mL. The combined effect of the season and herd stage of lactation explained 53.5% of the variation in bulk milk SCC. Fat and protein contents varied significantly with season and stage of lactation, and the association with SCC was non-significant for fat content and explained less than 3% of the variation in protein content. Lactose content was associated with SCC, stage of lactation, and season. Total bacterial count was associated with SCC and the indoor seasons. Determination of normal seasonal variation of goat bulk milk SCC is necessary to establish thresholds for defining milk as abnormal and unacceptable for further processing and improving the usefulness of SCC as a tool for milk quality improvement in dairy goats. The results suggest that SCC thresholds for taking action to improve the milk quality should be adjusted for season and stage of lactation.

Estimation of epidemiological cut-off values for eight antibiotics used for treatment of bovine mastitis caused by Streptococcus uberis and Streptococcus dysgalactiae subsp. dysgalactiae.

Interpretive criteria for antimicrobial susceptibility testing are lacking for most antimicrobials used for bovine streptococcal mastitis. The objectives of this study were to determine (tentative) epidemiological cut-off ((T)ECOFF) values for clinically relevant antibiotics used for treatment of bovine mastitis, and to estimate the proportion of acquired resistance (non-wild-types) in Streptococcus dysgalactiae subsp. dysgalactiae and Streptococcus uberis. A total of 255 S. uberis and 231 S. dysgalactiae subsp. dysgalactiae isolates were obtained in Denmark and Norway from bovine mastitis. The isolates were tested for susceptibility to 10 antibiotics using broth microdilution. In accordance with the European Committee on Antimicrobial Susceptibility Testing (EUCAST) standard operating procedure, additional published MIC distributions were included for the estimation of ECOFFs for cloxacillin, cephapirin, lincomycin and tylosin, and TECOFFs for amoxicillin, benzylpenicillin, cephapirin and oxytetracycline. The proportion of non-wild-type (NWT) isolates for the beta-lactams was significantly higher in the Danish S. uberis (45-55%) compared to the Norwegian isolates (10-13%). For oxytetracycline, the proportion of NWT was significantly higher in the Danish isolates, both for S. uberis (28% vs. 3%) and S. dysgalactiae (22% vs. 0%). A bridging study testing in parallel MICs in a subset of isolates (n = 83) with the CLSI-specified and the EUCAST-specified broths showed excellent correlation between the MICs obtained with the two methods. The new ECOFFs and TECOFFs proposed in this study can be used for surveillance of antimicrobial resistance, and - for antimicrobials licensed for streptococcal bovine mastitis - as surrogate clinical breakpoints for predicting their clinical efficacy for this indication.

Prevalence of udder pathogens in milk samples from Norwegian dairy cows recorded in a national database in 2019 and 2020.

BACKGROUND: Identification of aetiological agents of mastitis in dairy cattle is important for herd management of udder health. In Norway, results from mastitis diagnostics are systematically recorded in a central database, so that the dairy industry can follow trends in the recorded frequency of udder pathogens and antimicrobial resistance patterns at national level. However, bacteriological testing of milk samples is based on voluntary sampling, and data are therefore subject to some bias. The aim of this study was to examine the prevalence of udder pathogens in Norwegian dairy cows by analysing data from the national routine mastitis diagnostics and to explore how routines for sampling and diagnostic interpretations may affect the apparent prevalence of different bacterial pathogens. We also assessed associations between udder pathogen findings and the barn- and milking systems of the herds. RESULTS: The most frequently detected major udder pathogens among all milk samples submitted for bacterial culture (n = 36,431) were Staphylococcus aureus (24.5%), Streptococcus dysgalactiae (13.3%) and Streptococcus uberis (9.0%). In the subset of samples from clinical mastitis (n = 7598); Escherichia coli (14.5%) was the second most frequently detected pathogen following S. aureus (27.1%). Staphylococcus epidermidis (10.0%), Corynebacterium bovis (9.4%), and Staphylococcus chromogenes (6.0%) dominated among the minor udder pathogens. Non-aureus staphylococci as a group, identified in 39% of the sampling events, was the most frequently identified udder pathogen in Norway. By using different definitions of cow-level bacterial diagnoses, the distribution of minor udder pathogens changed. Several udder pathogens were associated with the barn- and milking system but the associations were reduced in strength when data were analysed from farms with a comparable herd size. S. aureus was associated with tiestall housing, E. coli and S. dysgalactiae were associated with freestall housing, and S. epidermidis was associated with automatic milking systems. Only 2.5% of the 10,675 tested S. aureus isolates were resistant to benzylpenicillin. Among the 2153 tested non-aureus staphylococci, altogether 34% were resistant to benzylpenicillin. CONCLUSIONS: This study presents the recorded prevalence of udder pathogens in Norway over a two-year period and assesses the possible impact of the sampling strategies, diagnostic methods and diagnostic criteria utilized in Norway, as well as associations with different housing and milking systems. The national database with records of results from routine mastitis diagnostics in Norway provides valuable information about the aetiology of bovine mastitis at population level and can reveal shifts in the distribution and occurrence of udder pathogens.

Sensitivity and specificity of bacterial culture, qPCR, and somatic cell count for detection of goats with Staphylococcus aureus intramammary infection using Bayesian latent class models.

Staphylococcus aureus (S. aureus) is an important udder pathogen affecting goat milk production. The ability to detect goats with subclinical mastitis caused by S. aureus is essential in udder health control programs. In Norway, the industry recommends using somatic cell count (SCC) as a screening tool, and conventional bacterial culture (BC) as a confirmatory test for goat milk samples, but a commercial qPCR, Mastitis 4 qPCR (DNA Diagnostics, Risskov, Denmark) is also available. However, few studies have validated the use of these methods for the detection of goats with S. aureus intramammary infection (IMI). Therefore, the objective of this retrospective study was to estimate the diagnostic sensitivity and specificity of BC, qPCR, and SCC for the detection of goats with IMI caused by S. aureus using Bayesian latent class analysis. We analyzed the BC and qPCR results of aseptically collected milk samples and SCC results from milk recording samples from 319 goats from three herds using different SCC cut-offs. At a SCC cut-off of 2000,000 cells/mL, the estimated median prevalence in each herd was 12.7% (95% highest posterior density credible interval [CI] 6.5-19.8), 15.7% (95% CI 9.3-23.0), and 1.5% (95% CI 0.0-4.3). The median sensitivity was 93.0% (95% CI 80.2-100), 93.6% (95% CI 82.3-100) and 78.2% (95% CI 62.3-91.2) for BC, qPCR, and SCC, respectively. The estimated median specificity of BC was 99.5% (99% CI 98.4-100), for qPCR, 98.9% (95% CI 97.5-100), and for SCC 61.5% (95% CI 56.0-67.1). The results show that BC, which is today's standard method for diagnosing IMI, has a high accuracy for detection of goats with S. aureus IMI, but qPCR had a sensitivity and specificity similar to BC, and may act as an alternative.

Longitudinal dynamics of the bovine udder microbiota.

BACKGROUND: In recent years, the number of studies concerning microbiota of the intramammary environment has increased rapidly due to the development of high-throughput sequencing technologies that allow mapping of microbiota without culturing. This has revealed that an environment previously thought to be sterile in fact harbours a microbial community. Since this discovery, many studies have investigated the microbiota of different parts of the udder in various conditions. However, few studies have followed the changes that occur in the udder microbiota over time. In this study, the temporal dynamics of the udder microbiota of 10 cows, five with a low somatic cell count (SCC, SCC < 100,000 cells/mL) and five with a high SCC (SCC > 100,000 cells/mL), were followed over 5 months to gather insights into this knowledge gap. RESULTS: Analysis of the temporal changes in the microbial composition of milk from udders with a low SCC revealed a dynamic and diverse microbiota. When an imbalance due to one dominating genus was recorded, the dominant genus quickly vanished, and the high diversity was restored. The genera dominating in the samples with a high SCC remained the dominant genera throughout the whole sampling period. These cows generally displayed a heightened SCC or an intramammary infection in at least one quarter though-out the sampling period. CONCLUSION: Our results show that the bovine udder has a diverse microbiota, and that the composition and diversity of this community affects udder health with regards to SCC. Understanding what influences the composition and stability of this community has important implications for the understanding, control, and treatment of mastitis.

Molecular detection and genotype characterization of Streptococcus dysgalactiae from sheep flocks with outbreaks of infectious arthritis.

Outbreaks of infectious arthritis in young lambs are a growing concern for the Norwegian sheep industry. In other countries, Streptococcus dysgalactiae subspecies dysgalactiae (SDSD) is a frequent cause of such outbreaks. The objectives of this study were to investigate the causes of outbreaks of infections arthritis in Norwegian sheep flocks, and describe the sources, colonization patterns and genetic diversity of SDSD in affected and healthy sheep flocks. Almost 2000 samples from joints, animal body sites and the indoor environment were analysed by qPCR and culturing for SDSD, which was detected in 27 of 30 flocks. The proportion of positive samples was greater in outbreak flocks compared to healthy flocks. Altogether, SDSD was detected in 48 % of the samples from lambs, 27 % of the samples from ewes and 48 % of environmental samples. A relatively high proportion (67 %) of ear tag wounds were SDSD positive. These wounds may provide a port of entry for SDSD. Whole genome sequencing revealed a clonal distribution of SDSD-isolates, and identified four different multi locus sequence types (STs), among which two STs, ST454 and ST531, dominated. These STs were found in geographically distant flocks. ST454 was almost exclusively found in outbreak flocks. The current study points to skin, wounds and mucous membranes of animals as the main reservoir of SDSD in sheep flocks. However, a significantly higher proportion of SDSD-positive environmental samples in outbreak flocks compared to healthy flocks suggests that also indirect transmission may play a role.

Whole genome sequencing reveals possible host species adaptation of Streptococcus dysgalactiae.

Streptococcus dysgalactiae (SD) is an emerging pathogen in human and veterinary medicine, and is associated with several host species, disease phenotypes and virulence mechanisms. SD has traditionally been divided into the subspecies dysgalactiae (SDSD) and subsp. equisimilis (SDSE), but recent molecular studies have indicated that the phylogenetic relationships are more complex. Moreover, the genetic basis for the niche versatility of SD has not been extensively investigated. To expand the knowledge about virulence factors, phylogenetic relationships and host-adaptation strategies of SD, we analyzed 78 SDSD genomes from cows and sheep, and 78 SDSE genomes from other host species. Sixty SDSD and 40 SDSE genomes were newly sequenced in this study. Phylogenetic analysis supported SDSD as a distinct taxonomic entity, presenting a mean value of the average nucleotide identity of 99%. Bovine and ovine associated SDSD isolates clustered separately on pangenome analysis, but no single gene or genetic region was uniquely associated with host species. In contrast, SDSE isolates were more heterogenous and could be delineated in accordance with host. Although phylogenetic clustering suggestive of cross species transmission was observed, we predominantly detected a host restricted distribution of the SD-lineages. Furthermore, lineage specific virulence factors were detected, several of them located in proximity to hotspots for integration of mobile genetic elements. Our study indicates that SD has evolved to adapt to several different host species and infers a potential role of horizontal genetic transfer in niche specialization.

Longitudinal Study of the Bulk Tank Milk Microbiota Reveals Major Temporal Shifts in Composition.

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.

Flock-level risk factors for outbreaks of infectious arthritis in lambs, Norway 2018.

BACKGROUND: Outbreaks of infectious arthritis in young lambs associated with Streptococcus dysgalactiae subspecies dysgalactiae (SDSD) lead to reduced animal welfare, increased use of antibiotics and economic losses for sheep farmers. Understanding risk factors is essential when developing strategies to prevent such outbreaks. This questionnaire-based cross-sectional study classified sheep flocks of respondents as cases or controls. Flock-level risk factors for outbreaks of infectious arthritis were assessed using a multivariable logistic regression model. RESULTS: Eighty-four of 1498 respondents (5.6%) experienced an outbreak of infectious arthritis in their flock in 2018, the year of study. Factors associated with a higher risk of outbreak were larger flock size (OR 1.3, 95% CI 1.1-1.4, per 100 lambs), plastic mesh flooring in the lambing pen (OR 3.0, 95% CI 1.7-5.3) and a lambing percentage greater than 200 (OR 2.0, 95% CI 1.1-3.5). Flocks where farmers observed infections around the ear tags of lambs also had an increased risk of outbreak (OR 2.6, 95% CI 1.6-4.3). CONCLUSIONS: The risk factors identified in this study are characteristic of modern and intensively managed sheep farms in Norway. A distinguishing feature of Norwegian sheep farming is winter housing and indoor lambing. One might expect that this in itself is a risk factor because of high stocking densities during lambing. However, outbreaks of infectious arthritis in young lambs are reported by the industry to be a more recent phenomenon. The current study indicates that intensification of indoor management systems with larger flocks and higher production per ewe may predispose to outbreaks. The results provide a basis for further studies on transmission dynamics of SDSD in sheep flocks with indoor lambing.