Economic effects of bovine mastitis and mastitis management: a review

Performance comparison of machine learning models used for predicting subclinical mastitis in dairy cows: Bagging, boosting, stacking, and super-learner ensembles versus single machine learning models

Mastitis has a substantial impact on the dairy industry across the world, causing dairy producers to suffer losses due to the reduced quality and quantity of produced milk. A further problem, related to this issue, is the excessive use of antibiotics that leads to the development of resistance in different bacterial strains. The growing consumer awareness oriented toward food safety and rational use of antibiotics has promoted the search for new methods of early identification of cows that may be at risk of developing the disease. Subclinical mastitis does not cause any visible changes to the udder or milk, and therefore it is more difficult to detect than clinical mastitis. The collection of large amounts of data related to milk performance of cows allows using machine learning (ML) methods to build models that could be used for classifying cows into healthy and at risk of subclinical mastitis. The data used for the purpose of this study included information from routine milk recording procedures. The dataset consisted of 19,856 records of 2,227 Polish Holstein-Friesian cows from 3 herds. The authors decided to use the approach of building ensemble ML models, in particular bagging, boosting, stacking, and super-learner models, and comparing them for accuracy of identification of disease-affected cows against single ML models based on the support vector machines, logistic regression, Gaussian Naive Bayes, k-nearest neighbors, and decision tree algorithms. The models were trained and evaluated based on the information recorded for herd 1 and using an 80:20 train-test split ratio according to animal ID (to avoid data leakage). The information recorded for herds 2 and 3 was only used to evaluate on unseen data models developed using the herd 1 dataset. Among the single ML models, the support vector machines model was found to be the most accurate in predicting subclinical mastitis at subsequent test day when used both for the training set (mean F1-score of 0.760) and the testing sets containing data for herds 1, 2, and 3 (F1-score of 0.778, 0.790, and 0.741 respectively). The gradient boosting model was found to be the best performing model among the ensemble ML models (F1-score of 0.762, 0.779, 0.791, and 0.723 for the training set and the testing sets, respectively). The super-learner model, featuring the most advanced design and logistic regression in the meta layer, achieved the highest mean F1-score of 0.775 during the cross validation; however, it was characterized by a slightly worse prediction accuracy of the testing sets (mean F1-score of 0.768, 0.790, and 0.693 for herds 1, 2 and 3 respectively). The study findings confirm the promising role of ensemble ML methods, which were found to be slightly superior with respect to most of the single ML models.

Retrospective evaluation of udder recovery of cows with subclinical mastitis following treatment with acoustic pulse technology (APT) on commercial dairy farms and its economic impact

Retrospective evaluation of udder recovery following treatment of the inflamed quarter with acoustic pulse technology (APT) of cows with subclinical mastitis was done on 4 Israeli commercial dairy farms. Here, we evaluated the APT treatment as a tool to manage subclinical mastitis and its economic consequences in commercial farms. Recovery of the infected glands following APT treatment was compared to the customary no-treatment (NT) for cows with subclinical mastitis. Over 2 years, 467 cows with subclinical mastitis were identified. Subclinical mastitis was defined by elevated somatic cell count (SCC; >1 × 106 cells/mL) in the monthly test-day milk sample; 222 cows were treated with APT and 245 cows were not treated and served as control. Differences between treatment groups in culling, milk quality, milk yield and bacterial elimination were analyzed. After treatment, cure from bacteria was calculated only for cows with pre-isolated bacteria. The percentage of sampled cows determined as cured (no bacterial finding) in the NT group was 32.7% (35/107) (30.9% Gram negative; 32.4% Gram positive) and in the APT-treated group, 83.9% (42/55) (89.4% Gram negative; 80.6% Gram positive). Culling rate due to mastitis was significantly lower (>90%) in the APT-treated vs. NT group. Recovery was 66.0% in the APT group compared to 11.5% in the NT group at 90 d post-treatment. Average milk volume per cow in the APT-treated group was 16.1% higher compared to NT cows. Based on the study, savings incurred by using APT to treat only subclinical cows per 100-cow herd can total $15,106/y, or $309 per treated subclinically infected cow.

Bacteriophage-derived endolysins as innovative antimicrobials against bovine mastitis-causing streptococci and staphylococci: a state-of-the-art review

Bacteriophage-encoded endolysins, peptidoglycan hydrolases breaking down the Gram-positive bacterial cell wall, represent a groundbreaking class of novel antimicrobials to revolutionize the veterinary medicine field. Wild-type endolysins exhibit a modular structure, consisting of enzymatically active and cell wall-binding domains, that enable genetic engineering strategies for the creation of chimeric fusion proteins or so-called 'engineered endolysins'. This biotechnological approach has yielded variants with modified lytic spectrums, introducing new possibilities in antimicrobial development. However, the discovery of highly similar endolysins by different groups has occasionally resulted in the assignment of different names that complicate a straightforward comparison. The aim of this review was to perform a homology-based comparison of the wild-type and engineered endolysins that have been characterized in the context of bovine mastitis-causing streptococci and staphylococci, grouping homologous endolysins with ≥ 95.0% protein sequence similarity. Literature is explored by homologous groups for the wild-type endolysins, followed by a chronological examination of engineered endolysins according to their year of publication. This review concludes that the wild-type endolysins encountered persistent challenges in raw milk and in vivo settings, causing a notable shift in the field towards the engineering of endolysins. Lead candidates that display robust lytic activity are nowadays selected from screening assays that are performed under these challenging conditions, often utilizing advanced high-throughput protein engineering methods. Overall, these recent advancements suggest that endolysins will integrate into the antibiotic arsenal over the next decade, thereby innovating antimicrobial treatment against bovine mastitis-causing streptococci and staphylococci.

Cows with diverging haplotypes show differences in differential milk cell count, milk parameters and vaginal temperature after S. aureus challenge but not after E. coli challenge

BACKGROUND

In dairy cattle, mastitis causes high financial losses and impairs animal well-being. Genetic selection is used to breed cows with reduced mastitis susceptibility. Techniques such as milk cell flow cytometry may improve early mastitis diagnosis. In a highly standardized in vivo infection model, 36 half-sib cows were selected for divergent paternal Bos taurus chromosome 18 haplotypes (Q vs. q) and challenged with Escherichia coli for 24 h or Staphylococcus aureus for 96 h, after which the samples were analyzed at 12 h intervals. Vaginal temperature (VT) was recorded every three minutes. The objective of this study was to compare the differential milk cell count (DMCC), milk parameters (fat %, protein %, lactose %, pH) and VT between favorable (Q) and unfavorable (q) haplotype cows using Bayesian models to evaluate their potential as improved early indicators of differential susceptibility to mastitis.

RESULTS

After S. aureus challenge, compared to the Q half-sibship cows, the milk of the q cows exhibited higher PMN levels according to the DMCC (24 h, p < 0.001), a higher SCC (24 h, p < 0.01 and 36 h, p < 0.05), large cells (24 h, p < 0.05) and more dead (36 h, p < 0.001) and live cells (24 h, p < 0.01). The protein % was greater in Q milk than in q milk at 0 h (p = 0.025). In the S. aureus group, Q cows had a greater protein % (60 h, p = 0.048) and fat % (84 h, p = 0.022) than q cows. Initially, the greater VT of S. aureus-challenged q cows (0 and 12-24 h, p < 0.05) reversed to a lower VT in q cows than in Q cows (48-60 h, p < 0.05). Additionally, the following findings emphasized the validity of the model: in the S. aureus group all DMCC subpopulations (24 h-96 h, p < 0.001) and in the E. coli group nearly all DMCC subpopulations (12 h-24 h, p < 0.001) were higher in challenged quarters than in unchallenged quarters. The lactose % was lower in the milk samples of E. coli-challenged quarters than in those of S. aureus-challenged quarters (24 h, p < 0.001). Between 12 and 18 h, the VT was greater in cows challenged with E. coli than in those challenged with S. aureus (3-h interval approach, p < 0.001).

CONCLUSION

This in vivo infection model confirmed specific differences between Q and q cows with respect to the DMCC, milk component analysis results and VT results after S. aureus inoculation but not after E. coli challenge. However, compared with conventional milk cell analysis monitoring, e.g., the global SCC, the DMCC analysis did not provide refined phenotyping of the pathogen response.

The effect of selective dry cow therapies based on two different algorithms on antimicrobial use, udder health, milk production, and culling in the absence of internal teat sealant use at dry-off

The objective of this study was to evaluate the effect of selective dry cow therapy (SDCT) strategies based on 2 different algorithms as compared with blanket dry-cow therapy for measures of udder health, milk yield, and culling in herds not using internal teat sealant. Cows from 2 commercial farms in West Texas were randomized into 3 different groups: SDCT Algorithm 1 (ALG1; n = 455) cows treated with an intramammary antimicrobial at dry-off if somatic cell count (SCC) > 200,000 cells/mL at any Dairy Herd Improvement Association (DHIA) test date or if the cow had 2 or more cases of clinical mastitis during the enrollment lactation; SDCT Algorithm 2 (ALG2; n = 458) cows treated with an intramammary antimicrobial at dry-off if SCC >200,000 cell/mL at last test date or any case of clinical mastitis during the enrollment lactation; Control cows (CON = 447) received blanket dry cow therapy. All cows enrolled in the study did not receive an internal or external teat sealant. Data related to milk and somatic cell count linear score (LSCC) was collected monthly. Milk yield and LSCC during the first 6 mo of lactation were analyzed using repeated measures ANOVA models, while Cox's Proportional Hazards models were fitted to culling and clinical mastitis data. The farm was fitted as a random effect in all models. The percentage of cows receiving antimicrobials at dry cow was 51.3, 24.7, and 100% for ALG1, ALG2, and CON, respectively. Treatment did not influence the IMI dynamics during the dry period. Additionally, no statistical differences related to treatment were observed for LSCC and milk yield. The LSCC for ALG1, ALG2, and CON was 2.44, 2.41, and 2.26, respectively. The average milk yield for ALG1, ALG2, and CON cows was 43.2, 43.2, and 44.0 kg/d, respectively. Treatment did not affect clinical mastitis incidence and culling. The cumulative incidence of clinical mastitis was 19.6%, 19.4%, and 21.4% for ALG1, ALG2, and CON cows respectively. Additionally, the cumulative risk of death or culling was 18.5%, 17.1%, and 19.5% for ALG1, ALG2, and CON cows respectively. In conclusion, SDCT strategies led to a decrease in antimicrobial drug use at dry-off, without significantly impacting the incidence of clinical mastitis, the risk of culling, LSCC and milk yield of dairy cows. However, numerical differences in LSCC and milk yield were observed between treatment groups.

Molecular and phenotypic identification of bacterial species isolated from cows with mastitis from three regions of Poland

BACKGROUND

Bovine mastitis is a widespread disease affecting dairy cattle worldwide and it generates substantial losses for dairy farmers. Mastitis may be caused by bacteria, fungi or algae. The most common species isolated from infected milk are, among others, Streptococcus spp., Escherichia coli, Staphylococcus aureus and non-aureus staphylococci and mammaliicocci. The aim of this paper is to determine the frequency of occurrence of bacterial species in milk samples from cows with mastitis from three regions of Poland: the north-east, the south-west and the south. To this end 203 milk samples taken from cows with a clinical form (CM) of mastitis (n = 100) and healthy animals (n = 103) were examined, which included culture on an appropriate medium followed by molecular detection of E. coli, S. aureus, Streptococcus agalactiae and Streptococcus uberis, as one of the most common species isolated from mastitis milk.

RESULTS

The results obtained indicated that S. uberis was the most commonly cultivated CM species (38%, n = 38), followed by S. aureus (22%, n = 22), E. coli (21%, n = 21) and S. agalactiae (18%, n = 18). Similar frequencies in molecular methods were obtained for S. uberis (35.1%) and S. aureus (28.0%). The variation of sensitivity of both methods may be responsible for the differences in the E. coli (41.0%, p = 0.002) and S. agalactiae (5.0%, p = 0.004) detection rates. Significant differences in composition of species between three regions of Poland were noted for E. coli incidence (p < 0.001), in both the culture and molecular methods, but data obtained by the PCR method indicated that this species was the least common in north-eastern Poland, while the culture method showed that in north-eastern Poland E. coli was the most common species. Significant differences for the molecular method were also observed for S. uberis (p < 0.001) and S. aureus (p < 0.001). Both species were most common in southern and south-western Poland.

CONCLUSIONS

The results obtained confirm the need to introduce rapid molecular tests for veterinary diagnostics, as well as providing important epidemiological data, to the best of our knowledge data on Polish cows in selected areas of Poland is lacking.

Survey of farm, parlour and milking management, parlour technologies, SCC control strategies and farmer demographics on Irish dairy farms

BACKGROUND

This cross-sectional study describes a survey designed to fill knowledge gaps regarding farm management practices, parlour management practices and implemented technologies, milking management practices, somatic cell count (SCC) control strategies, farmer demographics and attitudes around SCC management on a sample of Irish dairy farms.

RESULTS

We categorized 376 complete responses by herd size quartile and calving pattern. The average respondent herd was 131 cows with most (82.2%) operating a seasonal calving system. The median monthly bulk tank somatic cell count for seasonal calving systems was 137,000 cells/ml (range 20,000 - 1,269,000 cells/ml), 170,000 cells/ml for split-calving systems (range 46,000 - 644,000 cells/ml) and 186,000 cells/ml for 'other' herds (range 20,000 - 664,000 cells/ml). The most common parlour types were swing-over herringbones (59.1%) and herringbones with recording jars (22.2%). The average number of units across herringbone parlours was 15, 49 in rotary parlours and two boxes on automatic milking system (AMS) farms. The most common parlour technologies were in-parlour feeding systems (84.5%), automatic washers on the bulk tank (72.8%), automatic cluster removers (57.9%), and entrance or exit gates controlled from the parlour pit (52.2%). Veterinary professionals, farming colleagues and processor milk quality advisors were the most commonly utilised sources of advice for SCC management (by 76.9%, 50.0% and 39.2% of respondents respectively).

CONCLUSIONS

In this study, we successfully utilised a national survey to quantify farm management practices, parlour management practices and technology adoption levels, milking management practices, SCC control strategies and farmer demographics on 376 dairy farms in the Republic of Ireland. Rotary and AMS parlours had the most parlour technologies of any parlour type. Technology add-ons were generally less prevalent on farms with smaller herds. Despite finding areas for improvement with regard to frequency of liner changes, glove-wearing practices and engagement with bacteriology of milk samples, we also found evidence of high levels of documentation of mastitis treatments and high use of post-milking teat disinfection. We discovered that Irish dairy farmers are relatively content in their careers but face pressures regarding changes to the legislation around prudent antimicrobial use in their herds.

Development of a prototypic, field-usable diagnostic tool for the detection of gram-positive cocci-induced mastitis in cattle

BACKGROUND

Bovine mastitis is one of the most widespread diseases affecting cattle, leading to significant losses for the dairy industry. Currently, the so-called gold standard in mastitis diagnosis involves determining the somatic cell count (SCC). Apart from a number of advantages, this method has one serious flaw: It does not identify the etiological factor causing a particular infection, making it impossible to introduce targeted antimicrobial therapy. This can contribute to multidrug-resistance in bacterial species. The diagnostic market lacks a test that has the advantages of SCC and also recognizes the species of pathogen causing the inflammation. Therefore, the aim of our study was to develop a lateral flow immunoassay (LFIA) based on elongation factor Tu for identifying most prevalent Gram-positive cocci responsible for causing mastitis including Streptococcus uberis, Streptococcus agalactiae and Staphylococcus aureus.

RESULTS

As a result, we showed that the assay for S. uberis detection demonstrated a specificity of 89.02%, a sensitivity of 43.59%, and an accuracy of 80.3%. In turn, the second variant - assay for Gram-positive cocci reached a specificity of 95.59%, a sensitivity of 43.28%, and an accuracy of 78.33%.

CONCLUSIONS

Our study shows that EF-Tu is a promising target for LFIA and we have delivered evidence that further evaluation could improve test parameters and fill the gap in the mastitis diagnostics market.

Inbreeding depression for producer-recorded udder, metabolic, and reproductive diseases in US dairy cattle

This study leveraged a growing dataset of producer-recorded phenotypes for mastitis, reproductive diseases (metritis and retained placenta), and metabolic diseases (ketosis, milk fever, and displaced abomasum) to investigate the potential presence of inbreeding depression for these disease traits. Phenotypic, pedigree, and genomic information were obtained for 354,043 and 68,292 US Holstein and Jersey cows, respectively. Total inbreeding coefficients were calculated using both pedigree and genomic information; the latter included inbreeding estimates obtained using a genomic relationship matrix and runs of homozygosity. We also generated inbreeding coefficients based on the generational inbreeding for recent and old pedigree inbreeding, for different run-of-homozygosity length classes, and for recent and old homozygous-by-descent segment-based inbreeding. Estimates on the liability scale revealed significant evidence of inbreeding depression for reproductive-disease traits, with an increase in total pedigree and genomic inbreeding showing a notable effect for recent inbreeding. However, we found inconsistent evidence for inbreeding depression for mastitis or any metabolic diseases. Notably, in Holsteins, the probability of developing displaced abomasum decreased with inbreeding, particularly for older inbreeding. Estimates of disease probability for cows with low, average, and high inbreeding levels did not significantly differ across any inbreeding coefficient and trait combination, indicating that although inbreeding may affect disease incidence, it likely plays a smaller role compared with management and environmental factors.

Comparative genomic analyses of Klebsiella pneumoniae K57 capsule serotypes isolated from bovine mastitis in China

Klebsiella pneumoniae can cause severe clinical mastitis in dairy cows, with K. pneumoniae type K57 (K57-KP) being the most common capsular serotype. To identify virulence factors and antimicrobial-resistance (AMR) genes of K57-KP with varying virulence, Galleria mellonella (greater wax moth) larvae were infected as a screening model to characterize virulence of 90 K57-KP strains, with 10 and 11 strains defined as virulent or attenuated, respectively, based on larval survival rates. Next, virulence of these 21 isolates was subsequently confirmed in adhesion and lactate dehydrogenase release assays, using bovine mammary epithelial cells cultured in vitro. Finally, genes associated with virulence and AMR were characterize with whole-genome sequencing. These 21 K57-KP strains were designated into 16 sequence types based on multi-locus sequence typing and allocated in phylogenetic analysis based on single nucleotide polymorphisms. We found great genetic diversity among isolates. In addition, adhesion-associated genes (e.g., fimA, sfaA, and focA) aminoglycoside-resistance genes (aph(6)-Id, strAB) were associated with virulence. This study provided new knowledge regarding virulence of K57-KP associated with bovine mastitis, which may inform development of novel diagnostic tools and prevention strategies for bovine mastitis.

An Explainable Deep Learning Classifier of Bovine Mastitis Based on Whole-Genome Sequence Data-Circumventing the p >> n Problem

The serious drawback underlying the biological annotation of whole-genome sequence data is the p >> n problem, which means that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). We propose a way to circumvent the problem by combining a LASSO logistic regression with deep learning to classify cows as susceptible or resistant to mastitis, based on single nucleotide polymorphism (SNP) genotypes. Among several architectures, the one with 204,642 SNPs was selected as the best. This architecture was composed of two layers with, respectively, 7 and 46 units per layer implementing respective drop-out rates of 0.210 and 0.358. The classification of the test data resulted in AUC = 0.750, accuracy = 0.650, sensitivity = 0.600, and specificity = 0.700. Significant SNPs were selected based on the SHapley Additive exPlanation (SHAP). As a final result, one GO term related to the biological process and thirteen GO terms related to molecular function were significantly enriched in the gene set that corresponded to the significant SNPs. Our findings revealed that the optimal approach can correctly predict susceptibility or resistance status for approximately 65% of cows. Genes marked by the most significant SNPs are related to the immune response and protein synthesis.

Bacillus velezensis iturins inhibit the hemolytic activity of Staphylococcus aureus

Bovine mastitis caused by S. aureus has a major economic impact on the dairy sector. With the crucial need for new therapies, anti-virulence strategies have gained attention as alternatives to antibiotics. Here we aimed to identify novel compounds that inhibit the production/activity of hemolysins, a virulence factor of S. aureus associated with mastitis severity. We screened Bacillus strains obtained from diverse sources for compounds showing anti-hemolytic activity. Our results demonstrate that lipopeptides produced by Bacillus spp. completely prevented the hemolytic activity of S. aureus at certain concentrations. Following purification, both iturins, fengycins, and surfactins were able to reduce hemolysis caused by S. aureus, with iturins showing the highest anti-hemolytic activity (up to 76% reduction). The lipopeptides showed an effect at the post-translational level. Molecular docking simulations demonstrated that these compounds can bind to hemolysin, possibly interfering with enzyme action. Lastly, molecular dynamics analysis indicated general stability of important residues for hemolysin activity as well as the presence of hydrogen bonds between iturins and these residues, with longevous interactions. Our data reveals, for the first time, an anti-hemolytic activity of lipopeptides and highlights the potential application of iturins as an anti-virulence therapy to control bovine mastitis caused by S. aureus.

Conditioner application improves bedding quality and bacterial composition with potential beneficial impacts for dairy cow's health

Recycled manure solids (RMS) is used as bedding material in cow housing but can be at risk for pathogens development. Cows spend several hours per day lying down, contributing to the transfer of potential mastitis pathogens from the bedding to the udder. The effect of a bacterial conditioner (Manure Pro, MP) application was studied on RMS-bedding and milk qualities and on animal health. MP product was applied on bedding once a week for 3 months. Bedding and teat skin samples were collected from Control and MP groups at D01, D51, and D90 and analyzed through 16S rRNA amplicon sequencing. MP application modified bacterial profiles and diversity. Control bedding was significantly associated with potential mastitis pathogens, while no taxa of potential health risk were significantly detected in MP beddings. Functional prediction identified enrichment of metabolic pathways of agronomic interest in MP beddings. Significant associations with potential mastitis pathogens were mainly observed in Control teat skin samples. Finally, significantly better hygiene and lower Somatic Cell Counts in milk were observed for cows from MP group, while no group impact was observed on milk quality and microbiota. No dissemination of MP strains was observed from bedding to teats or milk.

IMPORTANCE

The use of Manure Pro (MP) conditioner improved recycled manure solids-bedding quality and this higher sanitary condition had further impacts on dairy cows' health with less potential mastitis pathogens significantly associated with bedding and teat skin samples of animals from MP group. The animals also presented an improved inflammation status, while milk quality was not modified. The use of MP conditioner on bedding may be of interest in controlling the risk of mastitis onset for dairy cows and further associated costs.

Assessing teat canal morphology in the dry period and during lactation by high-resolution ultrasound

Our objectives were to quantify the dimensions of a fully 'closed' teat canal in dry cows and to describe recovery of the teat canal between milkings in lactating cows to assess whether and when full closure is attained, since this is an important determinant of udder health. Using an ultrasound scanner, teat canal length and diameter (proximal, midpoint and distal), teat cistern width, teat end width, whole teat width and teat wall thickness in 77 dry and 39 lactating dairy cows were measured. The dry cows represented a cross section of the dry population, with days since dry off ranging from 0 to 69 (median: 27). Data from lactating cows were recorded just before milking, and every 3 h post-milking. To control for location a cross-over (parlour vs. barn) study design was used. In dry cows, teat canal length and diameter did not vary by quarter or days since dry off, but multiparous cows had significantly wider teat canals than primiparous cows. The dry cow measurements can be used as baseline for dimensions for closed teats. In lactating cows, all teat dimensions except teat end width changed significantly during the 12-h milking cycle. Location (parlour vs. barn) did not affect the measurements, except teat end width and teat wall thickness. Teat canal length increased after milking and returned to pre-milking values by 9 h. Proximal and midpoint teat canal diameters decreased slightly just after milking and then progressively increased to above the pre-milking values by 9 h. Distal teat canal diameter increased after milking, partially contracting by 9 h. We found that during the dry period the teat canal is in a steady state, but its diameter is not zero, while during the lactation, the teat canal is in a near constant state of remodelling.

Using registry data to identify individual dairy cows with abnormal patterns in routinely recorded somatic cell counts

Data from the Danish milk recording system routinely enter the Danish Cattle Database, including somatic cell counts (SCC) for individual animals. Elevated SCC can signal intramammary inflammation, suggesting subclinical mastitis. Detecting mastitis is pivotal to limit severity, prevent pathogen spread, and target treatment or culling. This study aimed to differentiate normal and abnormal SCC patterns using recorded registry data. We used registry data from 2010 to 2020 for dairy cows in herds with 11 annual milk recordings. To create consistency across herds, we used data from 13,996 unique animals and eight different herds, selected based on the amount of data available, only selecting Holstein animals and conventional herds. We fitted log10-transformed SCC to days in milk (DIM) using the Wilmink and Wood's curve functions, originally developed for milk yield over the lactation. We used Nonlinear Least Square and Nonlinear Mixed Effect models to fit the log10-transformed SCC observations to DIM at animal level. Using mean squared residuals (MSR), we found a consistently better fit using a Wood's style function. Detection of MSR outliers in the model fitting process was used to identify animals with log10(SCC) curves deviating from the expected "normal" curve for that same animal. With this study, we propose a method to identify single animals with SCC patterns that indicate abnormalities, such as mastitis, based on registry data. This method could potentially lead to a registry data-based detection of mastitis cases in larger dairy herds.

Economic losses caused by mastitis and the influence of climate variation on the occurrence of the disease in a dairy cattle farm in southern Brazil

This study evaluated the economic impacts caused by mastitis in a small dairy farm with similar characteristics and production to most dairy farms in southern Brazil and investigated if climatic variations influenced mastitis occurrence in the region. A farm with, on average, 45 lactating Holstein cattle was monitored from November 2021 to October 2022, and data on mastitis cases, bulk tank milk somatic cell count, animal treatment costs, milk production, animal disposal costs, and production losses were collected. Monthly averages of temperature, relative humidity (RH), and rainfall in the region were obtained. The greatest loss was related to the drop in milk production, resulting in 63.8% of total losses, followed by animal disposal (29.5%), milk disposal (4.6%), and treating animals with mastitis (2.0%), totaling a 10.6% reduction in the annual gross income. There were negative correlations between the clinical mastitis rate and monthly RH and between subclinical mastitis and temperature; the occurrence of subclinical mastitis and average RH were positively correlated. Our findings showed that mastitis negatively impacted the economy and that climate influenced mastitis occurrence.

Understanding mastitis: Microbiome, control strategies, and prevalence - A comprehensive review

Mastitis significantly affects the udder tissue in dairy cattle, leading to inflammation, discomfort, and a decline in both milk yield and quality. The condition can be attributed to an array of microbial agents that access the mammary gland through multiple pathways. The ramifications of this ailment are not merely confined to animal welfare but extend to the financial viability of the livestock industry. This review offers a historical lens on mastitis, tracing its documentation back to 1851, and examines its global distribution with a focus on regional differences in prevalence and antimicrobial resistance (AMR) patterns. Specific microbial genes and communities implicated in both mastitis and AMR are explored, including Staphylococcus aureus, Streptococcus agalactiae,Streptococcus dysagalactiae, Streptococcus uberis Escherichia coli, Klebsiella pneumoniae, Mycoplasma bovis, Corynebacterium bovis, among others. These microorganisms have evolved diverse strategies to elude host immune responses and neutralize commonly administered antibiotics, complicating management efforts. The review aims a comprehensive overview of the current knowledge and research gaps on mastitis and AMR, and to highlight the need for a One Health approach to address this global health issue. Such an approach entails multi-disciplinary cooperation to foster judicious antibiotic use, enhance preventive measures against mastitis, and bolster surveillance and monitoring of AMR in pathogens responsible for mastitis.

The inhibition effect of caffeic acid on NOX/ROS-dependent macrophages M1-like polarization contributes to relieve the LPS-induced mice mastitis

The mammary gland is an adipose tissue containing not only adipocytes but also epithelial, endothelial, and immune cells. Epithelial cells and macrophages, as the integral components of the immune system, are on the front line of defense against infection. Our preliminary work proved that caffeic acid (CA) can effectively inhibit the inflammatory cascade of bovine mammary epithelial cells (BMEC) induced by lipopolysaccharide (LPS) and maintain cellular integrity and viability. Here, we investigated the therapeutic effect of CA on LPS-induced mice mastitis and explored its regulatory mechanism on macrophage inflammatory response induced by LPS in vitro. Firstly, the mice mastitis model was established by intramammary injection with 10 μg LPS, after which different CA doses (5, 10, 15 mg/kg) were administered. Then, the pathological section, myeloperoxidase (MPO) activity, proinflammatory factors and chemokines releasement, and redox state of mammary tissues were assessed, confirming CA's effectiveness on mice mastitis. In vitro, we validated the therapeutic relevance of CA in relieving LPS-induced RAW264.7 inflammatory and oxidative stress responses. Moreover, we further provided evidence that CA significantly reduced LPS-induced reactive oxygen species (ROS) generation via NADPH oxidase (NOX), which improved the imbalance relationship between nuclear factor kappa-B (NF-κB) and NF-E2 p45-related factor 2 (Nrf2) and led to a marked weakening of M1 polarization. The NOX-ROS signal inhibited by CA weakened the oxidative burst and neutrophil chemotaxis of macrophages, thus alleviating the immune cascade in mammary gland tissue and reducing the LPS-induced inflammatory damage. Collectively, CA would be a potential candidate or antibacterial synergist for curbing mastitis.

The Prediction of Clinical Mastitis in Dairy Cows Based on Milk Yield, Rumination Time, and Milk Electrical Conductivity Using Machine Learning Algorithms

In commercial dairy farms, mastitis is associated with increased antimicrobial use and associated resistance, which may affect milk production. This study aimed to develop sensor-based prediction models for naturally occurring clinical bovine mastitis using nine machine learning algorithms with data from 447 mastitic and 2146 healthy cows obtained from five commercial farms in Northeast China. The variables were related to daily activity, rumination time, and daily milk yield of cows, as well as milk electrical conductivity. Both Z-standardized and non-standardized datasets pertaining to four specific stages of lactation were used to train and test prediction models. For all four subgroups, the Z-standardized dataset yielded better results than those of the non-standardized one, with the multilayer artificial neural net algorithm showing the best performance. Variables of importance had a similar rank in this algorithm, indicating the consistency of these variables as predictors for bovine mastitis in commercial farms with similar automatic systems. Moreover, the peak milk yield (PMY) of mastitic cows was significantly higher than that of healthy cows (p < 0.005), indicating that high-yielding cattle are more prone to mastitis. Our results show that machine learning algorithms are effective tools for predicting mastitis in dairy cows for immediate intervention and management in commercial farms.

Economic impact of treatment of subclinical mastitis in early lactation using intramammary nisin

Treatment of subclinical mastitis (SCM) during lactation is rarely recommended due to concerns related to both antimicrobial usage and costs associated with milk discard. Nisin is a naturally produced antimicrobial peptide with a Gram-positive spectrum that, when given to dairy cows, does not require milk discard. We evaluated the economic impact of treatment of SCM during early lactation using a nisin-based intramammary treatment under different scenarios which included various treatment costs, milk prices, and cure rates. We stochastically simulated the dynamics of SCM detected during the first week of lactation. The net economic impact was expressed in US dollars per case. The probabilities of an event and their related costs were estimated using a model that was based on pathogen-specific assumptions selected from peer-reviewed articles. Nisin cure rates were based on results of pivotal studies included in the FDA approval submission. Based on our model, the average cost of a case of intramammary infection (i.e., only true positive cases) in early lactation was $170 (90th percentage range = $148 to $187), while the cost of a clinical mastitis case was $521 (90th percentage range = $435 to $581). Both estimates varied with etiology, parity, and stage of lactation. When comparing the net cost of SCM cases (i.e., CMT-positive tests) detected during the first week of lactation, nisin treatment generated an average positive economic impact of $19 per CMT-positive case. Use of nisin to treat SCM was beneficial 93% of the time. Based on the sensitivity analysis, treatment would result in an economically beneficial outcome for 95% and 73% of multiparous and primiparous cows, respectively. At the herd level, use of intramammary nisin to treat SCM in cows in early lactation was economically beneficial in most tested scenarios. However, economic impact was highly influenced by factors such as rate of bacteriological cure, cost of treatment, and parity of affected animal. These factors should be considered when deciding to use nisin as a treatment for SCM.

Alternative Traits for Genetic Evaluation of Mastitis Based on Lifetime Merit

Genetic selection has achieved little progress in reducing mastitis incidence. Mastitis traits are problematic due to the lack of sensitivity of the data and reliance on clinical diagnosis, often missing subclinical cases, and/or on monthly somatic cell count (SCC) measurements. The current measure for mastitis is the lactation average of the somatic cells score (LSCS). We studied two datasets: (1) 148 heifers divided into non-intramammary infected, sub-clinically infected and clinical mastitis groups; (2) data from 89,601 heifers from Israeli Holsteins through the same period divided into "udder healthy" (UH) and "non-healthy" (UNH) by a threshold of SCC 120,000 cells/mL in all nine monthly milk recordings. In study 1, non-infected heifers had significantly (p < 0.05) more partum, production days and overall lifetime milk production compared to clinical and sub-clinically infected. In study 2, UH heifers (20.3%) had significantly higher (p < 0.01) lifetime milk, production days, and lactations. Subdividing datasets by sires, the same analyses detected differences in percentages of UH daughters between the sire groups. Lifetime milk production correlated (r = +0.83, p < 0.001) with udder health status. SCC threshold of less than 120,000 cells/mL during all first lactation measurements indicated healthy udder, providing a valuable insight that this dichotomous trait is advantageous for calculating lifetime net-merit index (NM$) over LSCS.

Mastitis impact on high-yielding dairy farm's reproduction and net present value

Poor udder health can have a negative impact on milk production and reproductive performance, which reduces the net present value (NPV) of dairy farms. The aim of this study is therefore to investigate the relationship between clinical mastitis and NPV and the financial impact of impaired reproductive function. For this purpose, 473 dairy cows were included in our study, 146 cows with clinical mastitis (CM group) and 327 clinically healthy cows (CH group) from a high-yielding dairy farm in Romania, milking approximately 780 dairy cows with an average milk production of 46 kg milk/day. We found that, in contrast to CH cows, CM cows had a significantly lower conception rate at first service (58.2% vs. 41.7%, p < 0.05), third service (45.3% vs. 30.2%, p < 0.05), and total services (49.2% vs. 36.4%, p < 0.05). However, this positive effect was not observed for the average days open, which were significantly lower in CM cows than in CH cows (112 ± 4.3 days vs. 142 ± 3.1 days, p < 0.05). The fact that the non-pregnant CH cows had higher somatic cell counts (>400,000 SCC/mL) in their milk around artificial insemination (AI) and 1 month earlier than the pregnant cows (<250,000 SCC/ml) supports the idea that poor uterine health affects the reproductive activity of high-yielding cows. However, by using the UW-DairyRepro$ decision support tool, we found that despite the impairment of reproductive function in dairy cows, the largest negative impacts on NPV are still the cost of milk loss (US$14,439.4/farm/year) and treatment costs (US$4,380/farm/year). We considered the costs associated with poor reproductive function in the CM group (US$3,577/farm/year) as an additional cost of mastitis. Finally, it appears that the impact of mastitis on reproduction is associated with a lower chance of conception than it is with a daily risk of services.

Exploring the sources of variation of electrical conductivity and total and differential somatic cell count in Italian Mediterranean buffaloes

In the buffalo dairy sector, a huge effort is still needed to improve mastitis prevention, detection, and management. Electrical conductivity (EC) and total somatic cell count (SCC) are well-known indirect indicators of mastitis. Differential somatic cell count (DSCC), which represents the proportion of neutrophils and lymphocytes on the total SCC, is instead a novel phenotype collected in the dairy cattle sector in the last lustrum. As little is known about this novel trait in dairy buffalo, in the present study we explored the nongenetic factors affecting DSCC, as well as EC and total somatic cell score (SCS), in the Italian Mediterranean buffalo. The data set used for the analysis included 14,571 test-day (TD) records of 1,501 animals from 6 herds, and climatic information of the sampling locations. The original data were filtered to exclude animals with less than 3 TD per lactation and, for the investigated traits, outliers beyond 4 standard deviations. In the statistical model we included the fixed effects of herd (6 classes), days in milk (DIM; 10 classes of 30 d, with the last being an open class until 360 d), parity (6 classes, from 1 to 6+), year-season of calving (11 classes, from summer 2019 to winter 2021/2022), year-season of sampling (9 classes, from spring 2020 to spring 2022), production level (4 classes based on quartiles of average milk yield by herd), and temperature-humidity index (THI; 4 classes based on quartiles, calculated using the average temperature and relative humidity of the 5 d before sampling). Average EC, SCS, and DSCC vary across herds. Considering DIM, greater EC values were observed at the beginning and the end of lactation; SCS was slightly lower, but DSCC was greater around the lactation peak. Increased EC, SCS, and DSCC levels with increasing parity were reported. Year-season calving and year-season sampling only slightly affected the variation of the investigated traits. Milk of high-producing buffaloes was characterized by lower EC and SCS mean values, nevertheless it had slightly greater DSCC percentages. Buffaloes grouped in the highest THI classes (classes 3 and 4) showed, on average, greater EC, SCS, and DSCC in comparison to the lower classes, especially to class 2. Results of the present study represent a preliminary as well as necessary step for the possible future inclusion of EC, SCS, or DSCC in breeding programs aimed to improve mastitis resistance in dairy buffaloes.

Exopolysaccharides produced by Bacillus spp. inhibit biofilm formation by Staphylococcus aureus strains associated with bovine mastitis

Bovine mastitis is a costly disease in the dairy sector worldwide. Here the objective was to identify and characterize anti-biofilm compounds produced by Bacillus spp. against S. aureus associated with bovine mastitis. Results showed that cell-free supernatants of three Bacillus strains (out of 33 analysed) reduced S. aureus biofilm formation by approximately 40 % without affecting bacterial growth. The anti-biofilm activity was associated with exopolysaccharides (EPS) secreted by Bacillus spp. The EPS decreased S. aureus biofilm formation in a dose-dependent manner, inhibiting biofilm formation by 83 % at 1 mg/mL. The EPS also showed some biofilm disruption activity (up to 36.4 %), which may be partially mediated by increased expression of the aur gene. The characterization of EPS produced by Bacillus velezensis 87 and B. velezensis TR47II revealed macromolecules with molecular weights of 31.2 and 33.7 kDa, respectively. These macromolecules were composed mainly of glucose (mean = 218.5 μg/mg) and mannose (mean = 241.5 μg/mg) and had similar functional groups (pyranose ring, beta-type glycosidic linkage, and alkynes) as revealed by FT-IR. In conclusion, this study shows the potential applications of EPS produced by B. velezensis as an anti-biofilm compound that could contribute to the treatment of bovine mastitis caused by S. aureus.

Innovative Elastomers with Antimicrobial Activity May Decrease Infection Risks during Milking

Contagious pathogens are very costly to dairy herds, and they may have zoonotic and reverse-zoonotic potentials and may contribute to the spread of antimicrobial resistance. One of the most important risk factors for spreading these infections is milking, when liner contamination may transfer the pathogens from infected to healthy cows. There is no effective protocol to prevent the transmission of infection without the segregation of infected cows. Recently, the availability of elastomers with patented antimicrobial components in their formulations has allowed the exploration of alternative methods to reduce the risk of infection. Two different types of elastomers (rubber and silicone) and nine different formulations were challenged with three major mastitis pathogens (S. aureus, S. agalactiae, and E. coli). The results that were obtained in this study were interesting and unexpected. Indeed, to our knowledge, this is the first study to show that basic rubber materials have intrinsic antimicrobial activity. Silicone elastomers did not exhibit the same levels of bactericidal activity, although they did exhibit some antibacterial capacity. A significant decrease in bacterial survival curves was observed for all the formulations tested when antimicrobial components were added. The different results observed for the various products are likely due to the different formulations and diverse manufacturing processes. The availability of these new materials that significantly reduce the bacterial load on the liner surface may reduce the risk of spreading intramammary infections during milking. This would be an important step forward in achieving global sustainability of dairy herds, consistent with the objectives of One Health, by reducing the risks of zoonotic diseases and antimicrobial treatments.

In-Line Detection of Clinical Mastitis by Identifying Clots in Milk Using Images and a Neural Network Approach

Automated milking systems (AMSs) already incorporate a variety of milk monitoring and sensing equipment, but the sensitivity, specificity, and positive predictive value of clinical mastitis (CM) detection remain low. A typical symptom of CM is the presence of clots in the milk during fore-stripping. The objective of this study was the development and evaluation of a deep learning model with image recognition capabilities, specifically a convolutional neural network (NN), capable of detecting such clots on pictures of the milk filter socks of the milking system, after the phase in which the first streams of milk have been discarded. In total, 696 pictures were taken with clots and 586 pictures without. These were randomly divided into 60/20/20 training, validation, and testing datasets, respectively, for the training and validation of the NN. A convolutional NN with residual connections was trained, and the hyperparameters were optimized based on the validation dataset using a genetic algorithm. The integrated gradients were calculated to explain the interpretation of the NN. The accuracy of the NN on the testing dataset was 100%. The integrated gradients showed that the NN identified the clots. Further field validation through integration into AMS is necessary, but the proposed deep learning method is very promising for the inline detection of CM on AMS farms.

The use of machine learning to predict somatic cell count status in dairy cows post-calving

Udder health remains a priority for the global dairy industry to reduce pain, economic losses, and antibiotic usage. The dry period is a critical time for the prevention of new intra-mammary infections and it provides a point for curing existing intra-mammary infections. Given the wealth of udder health data commonly generated through routine milk recording and the importance of udder health to the productivity and longevity of individual cows, an opportunity exists to extract greater value from cow-level data to undertake risk-based decision-making. The aim of this research was to construct a machine learning model, using routinely collected farm data, to make probabilistic predictions at drying off for an individual cow's risk of a raised somatic cell count (hence intra-mammary infection) post-calving. Anonymized data were obtained as a large convenience sample from 108 UK dairy herds that undertook regular milk recording. The outcome measure evaluated was the presence of a raised somatic cell count in the 30 days post-calving in this observational study. Using a 56-farm training dataset, machine learning analysis was performed using the extreme gradient boosting decision tree algorithm, XGBoost. External validation was undertaken on a separate 28-farm test dataset. Statistical assessment to evaluate model performance using the external dataset returned calibration plots, a Scaled Brier Score of 0.095, and a Mean Absolute Calibration Error of 0.009. Test dataset model calibration performance indicated that the probability of a raised somatic cell count post-calving was well differentiated across probabilities to allow an end user to apply group-level risk decisions. Herd-level new intra-mammary infection rate during the dry period was a key driver of the probability that a cow had a raised SCC post-calving, highlighting the importance of optimizing environmental hygiene conditions. In conclusion, this research has determined that probabilistic classification of the risk of a raised SCC in the 30 days post-calving is achievable with a high degree of certainty, using routinely collected data. These predicted probabilities provide the opportunity for farmers to undertake risk decision-making by grouping cows based on their probabilities and optimizing management strategies for individual cows immediately after calving, according to their likelihood of intra-mammary infection.

Short milking tube thermogram analysis: an indicator of mastitis in Murrah buffaloes

In the present study, thermal images of the short milking tube of the milking machine representing four udder quarters independently attached to a milking animal, along with pre-milking and post-milking udder and teat thermograms, were taken using a hand-held digital infrared thermal camera (DarviDTL007) during morning milking of lactating Murrah buffaloes (n = 132) to assess the mastitis status. California mastitis test (CMT) and somatic cell count (SCC) of milk samples were carried out to screen the udder quarters as healthy, subclinical (SCM), and clinical mastitis (CM). The thermograms revealed an increase (p < 0.05) of 2.19 and 3.72ºC in the mean values of short milking tube (SMT) surface temperature among SCM and CM quarters compared to healthy quarters, respectively. The mean values of udder skin surface temperature (USST) for pre-milking, milking, and post-milking of SCM and CM compared to healthy quarters showed an increase (p < 0.05) of 2.17, 1.96, and 1.61ºC and 3.11, 2.88, and 2.73ºC, respectively. Similarly, compared to healthy quarters, the mean values of teat skin surface temperature (TSST) for pre-milking and post-milking of SCM and CM showed an increase (p < 0.05) of 2.12 and 1.66ºC and 3.07 and 2.45ºC, respectively. Also, CMT and SCC results showed a strong positive correlation (r = 0.68-0.91, p < 0.01) with all the thermographic parameters. Thus, thermograms of SMT alone can be used as an efficient detection tool in assessing SCM among Murrah buffaloes.

Variation in partial direct costs of treating clinical mastitis among 37 Wisconsin dairy farms

The objective of this observational study was to describe variations in partial direct costs of clinical mastitis (CM) treatments among 37 dairy herds using data obtained from herd management records. Animal health and drug purchase records were retrospectively collected from 37 Wisconsin dairy herds for a period of 1 yr. Each farm was visited to verify case definitions, recording accuracy, and detection criteria of CM cases. Descriptive statistics were used to summarize cost of drugs and milk discard. Differences in costs among protocols, intramammary (IMM) products, parities, days in milk, and recurrence were analyzed using ANOVA. Of 20,625 cases of CM, 31% did not receive antimicrobial treatment. The average cost of drugs and milk discard (including cases that were not treated) was $192.36 ± 8.90 (mean ± SE) per case and ranged among farms from $118.13 to $337.25. For CM cases treated only with IMM antimicrobials, milk discard accounted for 87% of total costs and was highly influenced by duration of therapy. Differences in costs were observed among parities, recurrence, and stage of lactation at case detection. Eight different treatment protocols were observed, but 64% of cases were treated using only IMM antimicrobials. Treatment costs varied among protocols; however, cases treated using both IMM and injectable antimicrobials as well as supportive therapy had the greatest costs as they were also treated for the longest duration. Ceftiofur was used for 82% of cases that received IMM antimicrobials while ampicillin was used for 51% of cases treated using injectable antimicrobials. With the exception of ceftiofur and pirlimycin IMM products, many IMM products were given for durations that exceeded the maximum labeled duration. For cases treated using only IMM therapy, as compared with observed costs, we estimated that partial direct costs could be reduced by $65.20 per case if the minimum labeled durations were used. Overall, partial direct costs per case varied among herds, cow factors, and treatment protocols and were highly influenced by the duration of therapy.

High-throughput analysis of CircRNA in cows with naturally infected Staphylococcus aureus mammary gland

Circular RNAs (CircRNA) are a special type of non-coding RNA molecule with a closed ring structure and are not affected by RNA exonucases. It has stable expression, is not easy to degrade, and exists in most eukaryotes. However, circRNA regulation of cow mastitis has not been widely recognized. Mammary epithelial tissues were collected from healthy Holstein cows (HCN) and mastitis Holstein cows (HCU). RNA sequencing (RNA SEQ) was performed for the differentially expressed circRNAs, and analysis results showed that 19 differentially expressed circRNAs were identified in HCN and HCU, among which 6 circRNAs were up-regulated and 13 circRNAs were down-regulated. We randomly selected nine circRNAs for Q-PCR verification, and the results showed consistent expression. Three circRNAs: circRNA2860, circRNA5323 and circRNA4027 were confirmed to be significantly differentially expressed circRNAs in cow mastitis. Also, their host genes TRPS1, SLC12A2 and MYH11 might be directly or indirectly play a role in cow mastitis. Furthermore, RNA polymerase transcription factor binding and tight junction are most enriched in GO and KEGG pathways, respectively. In addition, the regulatory network of circRNA-miRNA has been inferred from a bioinformatics perspective, which may help to understand the underlying molecular mechanism of circRNAs involved in regulating mastitis in cows.

Droplet digital PCR quantification of selected microRNAs in raw mastitic cow's milk from the west of Poland

Introduction

MicroRNAs (miRNAs), a class of noncoding small RNAs, have been recognised as potential biomarkers of mammary gland conditions, including bovine mastitis diagnosis. The aim of this study was to quantify selected miRNAs in the milk of mastitic cows.

Material and Methods

Milk samples (n = 90) were collected from healthy and mastitic dairy cows originating from local dairy cattle farms located in the west of Poland. MicroRNAs of the miR-21a, miR-92a, miR-146a and miR-383 species were quantified using the highly sensitive droplet digital PCR method. Direct measurement of somatic cell count (SCC) was performed using a cell counter. Cows were divided into three groups: those with an SCC below 200,000/mL were designated Low (n = 25), those with an SCC between 200,000 and 999,999 were Medium (n = 34), and those with an SCC of 1,000,000 or higher were High (n = 31). Microbiological analyses were performed using standard culture testing.

Results

The level of miR-383 was very low and this miRNA was excluded from analysis. The miR-92a was used to normalise miR-21a and miR-146a expression levels. The obtained results of expression of miR-21a and miR-146a correlated with somatic cell number (R = 0.53 and 0.79, respectively).

Conclusion

These results show that ddPCR is a useful method for quantifying miRNAs in raw cow milk. It seems that miR-146a is a promising marker for bovine mastitis, although further studies are needed to select a panel of miRNAs that can be used in mastitis monitoring in Poland.

Survey of Genotype Diversity, Virulence, and Antimicrobial Resistance Genes in Mastitis-Causing Streptococcus uberis in Dairy Herds Using Whole-Genome Sequencing

Streptococcus uberis is one of the primary causative agents of mastitis, a clinically and economically significant disease that affects dairy cattle worldwide. In this study, we analyzed 140 S. uberis strains isolated from mastitis milk samples collected from 74 cow herds in the Czech Republic. We employed whole-genome sequencing to screen for the presence of antimicrobial resistance (AMR) genes and genes encoding virulence factors, and to assess their genetic relationships. Our analysis revealed the presence of 88 different sequence types (STs), with 41% of the isolates assigned to global clonal complexes (GCCs), the majority of which were affiliated with GCC5. The STs identified were distributed across the major phylogenetic branches of all currently known STs. We identified fifty-one putative virulence factor genes, and the majority of isolates carried between 27 and 29 of these genes. A tendency of virulence factors and AMR genes to cluster with specific STs was observed, although such clustering was not evident within GCCs. Principal component analysis did not reveal significant diversity among isolates when grouped by GCC or ST prevalence. The substantial genomic diversity and the wide array of virulence factors found in S. uberis strains present a challenge for the implementation of effective anti-mastitis measures.

A Cross-Sectional Study of Risk Factors Affecting Milk Quality in Dairy Cows

Despite years of research devoted to bovine mastitis, the disease remains a serious problem in dairy cattle, causing economic losses to the dairy industry worldwide due to reduced milk yield, lower milk quality, drug costs and early culling of cows. The aim of this study is to determine the importance of several risk factors affecting milk quality in dairy cows, as well as to highlight proper milking techniques. A cross-sectional study was performed in one Greek dairy farm with the inclusion of a total of 1004 Holstein Friesian cows in the study. The udder and teat traits were recorded for each cow, while individual milk samples were used to estimate the somatic cell count (SCC) and gross milk composition. The traits recorded were examined as potential risk factors affecting milk quality using the Akaike information criterion (AIC) and the algorithm stepAIC to select the best linear regression model which explains the data. Overall, the prevalence of mastitis was ca. 9%. With an increase in the lactation period, the SCC increased (p ≤ 0.05) while fat (p ≤ 0.05), protein (p ≤ 0.001) and lactose (p ≤ 0.001) content decreased. Teat hyperkeratosis increased the SCC (p ≤ 0.05) and decreased P content (p ≤ 0.05). Proper husbandry management and milking procedures are considered essential to maintain milk quality of high standards.

Genotypic and antimicrobial susceptibility of Streptococcus agalactiae causing bovine mastitis in the central region of Thailand

Introduction

Streptococcus agalactiae is a highly contagious pathogen that causes bovine mastitis, leading to significant economic losses. This study aimed to (1) identify and characterize S. agalactiae strains responsible for bovine mastitis by examining their phenotypic and genotypic characteristics in Thai dairy-intensive farming areas and (2) determine their susceptibility profiles to antimicrobial agents.

Material and methods

In total, 100 S. agalactiae isolates obtained from clinical and subclinical mastitis cases from 13 dairy herds located in the central region of Thailand were examined. To confirm the identity of the bacterial pathogens, conventional microbiological procedures recommended by the National Mastitis Council (NMC) and the VITEK® 2 system were employed.

Results

All 100 isolates were successfully identified as S. agalactiae using the NMC procedure, whereas 94 isolates were identified as S. agalactiae using the VITEK® 2 system. Finally, the S. agalactiae-specific gene dlt S was identified in all the examined isolates using polymerase chain reaction. Capsular polysaccharide (CPS) typing revealed that all strains belonged to CPS type Ia. Multilocus sequence typing identified 33 selected isolates as sequence type 103. Random amplified polymorphic DNA (RAPD) typing yielded 43 RAPD types, with 6 RAPD clusters identified. These results demonstrated a high level of genetic diversity among S. agalactiae within the studied herds. RAPD analysis suggested that specific S. agalactiae strains could persist in dairy farms for 2-12 months. Furthermore, antimicrobial susceptibility testing was performed using the broth microdilution method. Most strains demonstrated susceptibility to ampicillin, penicillin, penicillin/novobiocin, cephalothin, oxacillin, ceftiofur, and erythromycin.

Discussion

This study revealed the phenotypic and genotypic characteristics of S. agalactiae isolates responsible for bovine mastitis in the central region of Thailand. The rapid identification of S. agalactiae and application of molecular typing methods can provide valuable epidemiological information regarding S. agalactiae causing mastitis in dairy farms. The antimicrobial susceptibility of S. agalactiae indicates that antimicrobial treatment for control and eradication could be a successful protocol. Our findings revealed that a single clonal strain of S. agalactiae affected the 13 studied farms. Further research is needed to explore the feasibility of vaccine development and application.

Subclinical Mastitis from Streptococcus agalactiae and Prototheca spp. Induces Changes in Milk Peptidome in Holstein Cattle

Early detection of bovine subclinical mastitis may improve treatment strategies and reduce the use of antibiotics. Herein, individual milk samples from Holstein cows affected by subclinical mastitis induced by S. agalactiae and Prototheca spp. were analyzed by untargeted and targeted mass spectrometry approaches to assess changes in their peptidome profiles and identify new potential biomarkers of the pathological condition. Results showed a higher amount of peptides in milk positive on the bacteriological examination when compared with the negative control. However, the different pathogens seemed not to trigger specific effects on the milk peptidome. The peptides that best distinguish positive from negative samples are mainly derived from the most abundant milk proteins, especially from β- and αs1-casein, but also include the antimicrobial peptide casecidin 17. These results provide new insights into the physiopathology of mastitis. Upon further validation, the panel of potential discriminant peptides could help the development of new diagnostic and therapeutic tools.

Proteomics and Genetic Approaches Elucidate the Circulation of Low Variability Staphylococcus aureus Strains on Colombian Dairy Farms

Staphylococcus aureus is one of the most prevalent pathogens causing bovine mastitis in the world, in part because of its ease of adaptation to various hosts and the environment. This study aimed to determine the prevalence of S. aureus in Colombian dairy farms and its relationship with the causal network of subclinical mastitis. From thirteen dairy farms enrolled, 1288 quarter milk samples (QMS) and 330 teat samples were taken from cows with positive (70.1%) and negative California Mastitis Test (CMT). In addition, 126 samples from the milking parlor environment and 40 from workers (nasal) were collected. On each dairy farm, a survey was conducted, and the milking process was monitored on the day of sampling. S. aureus was identified in 176 samples, i.e., 138 QMS, 20 from teats, 8 from the milking parlor environment, and 10 from workers' nasal swabs. Isolates identified as S. aureus underwent proteomics (clustering of mass spectrum) and molecular (tuf, coa, spa Ig, clfA, and eno genes) analysis. Regarding proteomics results, isolates were distributed into three clusters, each with members from all sources and all farms. Concerning molecular analysis, the virulence-related genes clfA and eno were identified in 41.3% and 37.8% of S. aureus isolates, respectively. We provide evidence on the circulation of S. aureus strains with limited variability among animals, humans, and the environment. The parameters with the lowest compliance in the farms which may be implicated in the transmission of S. aureus are the lack of handwashing and abnormal milk handling.

Antimicrobial Susceptibility and Resistance Genes in Streptococcus uberis Isolated from Bovine Mastitis in the Czech Republic

Streptococcus uberis is one of the most important causative agents of mastitis and is a common reason for the use of antimicrobials in dairy cows. In this study, we assessed the antimicrobial susceptibility of 667 S. uberis isolates originating from 216 Czech dairy farms collected between 2019 and 2023 using the broth microdilution method. We tested 140 of the isolates for the presence of antimicrobial genes using whole-genome sequencing and evaluated their relationship with phenotypic resistance. Streptococcus uberis isolates showed high levels of resistance to tetracycline (59%), followed by streptomycin (38%) and clindamycin (29%). Although all of the isolates were susceptible to beta-lactams, a relatively high percentage of intermediately susceptible isolates was recorded for ampicillin (44%) and penicillin (18%). The isolates were mainly resistant to tetracycline alone (31.3%); the second most frequent occurrence of the phenotypic profile was simultaneous resistance to tetracycline, streptomycin, and clindamycin (16.6%). The occurrence of antibiotic resistance genes did not always match the phenotypic results; in total, 36.8% of isolates that possessed the ant(6)-Ia gene did not show phenotypic resistance to streptomycin. To a lesser extent, silent genes were also detected in clindamycin and tetracycline. This study confirmed the high susceptibility of S. uberis to penicillins used as first-line antimicrobials for S. uberis mastitis treatment.

Mammary Epithelial Cell-Derived Exosomal miR-221-3p Regulates Macrophage Polarization by Targeting Igf2bp2 during Mastitis

Mastitis affects the milk quality and yield and is the most expensive disease in dairy cows. Elucidation of the pathogenesis of mastitis is of great importance for disease control. As a medium of intercellular communication, exosomes play key roles in various inflammatory diseases by regulating macrophage polarization. However, the molecular factors in exosomes that mediate the intercellular communication between mammary epithelial cells and macrophages during mastitis remain to be further explored. In this study, we isolated and identified mammary epithelial cell-derived exosomes from a lipopolysaccharide (LPS)/lipoteichoic acid (LTA)-induced mastitis cell model, and we demonstrated that exosomes from LPS/LTA-stimulated mammary epithelial cells promote M1-type macrophage polarization in vivo and in vitro. Based on the results of high-throughput sequencing, we constructed a differential miRNA (microRNA) expression profile of exosomes and demonstrated that miR-221-3p was highly expressed. Furthermore, in vivo and in vitro experiments, combined with coculture experiments and fluorescence tracing, showed that high miR-221-3p expression promoted M1-type macrophage polarization, demonstrating the transcellular role of miR-221-3p. Mechanistically, dual luciferase reporter gene assays and rescue assays showed that miR-221-3p regulated macrophage polarization by targeting Igf2bp2. The results of this study will deepen our understanding of the pathogenesis of mastitis, and the molecular regulatory axis that was established in this study is expected to be a target for mastitis treatment.

CowMesh: a data-mesh architecture to unify dairy industry data for prediction and monitoring

Dairy is an economically significant industry that caters to the huge demand for food products in people's lives. To remain profitable, farmers need to manage their farms and the health of the dairy cows in their herds. There are, however, many risks to cow health that can lead to significant challenges to dairy farm management and have the potential to lead to significant losses. Such risks include cow udder infections (i.e., mastitis) and cow lameness. As automation and data recording become more common in the agricultural sector, dairy farms are generating increasing amounts of data. Recently, these data are being used to generate insights into farm and cow health, where the objective is to help farmers manage the health and welfare of dairy cows and reduce losses from cow health issues. Despite the level of data generation on dairy farms, this information is often difficult to access due to a lack of a single, central organization to collect data from individual farms. The prospect of such an organization, however, raises questions about data ownership, with some farmers reluctant to share their farm data for privacy reasons. In this study, we describe a new data mesh architecture designed for the dairy industry that focuses on facilitating access to data from farms in a decentralized fashion. This has the benefit of keeping the ownership of data with dairy farmers while bringing data together by providing a common and uniform set of protocols. Furthermore, this architecture will allow secure access to the data by research groups and product development groups, who can plug in new projects and applications built across the data. No similar framework currently exists in the dairy industry, and such a data mesh can help industry stakeholders by bringing the dairy farms of a country together in a decentralized fashion. This not only helps farmers, dairy researchers, and product builders but also facilitates an overview of all dairy farms which can help governments to decide on regulations to improve the dairy industry at a national level.

Review: Linking animal health measures in dairy cows to farm-level economic outcomes: a systematic literature mapping

Farm animal health is an area of increasing interest to both the public and industry stakeholders. There is an ongoing debate on whether improving animal health, and thereby increasing welfare, is profitable or not. Improving animal health often requires investments in the farm or increases labour costs. As a result, the impact of animal health on farm economy is particularly interesting. This study systematically maps and assesses the available evidence in the published scientific literature regarding the link between farms' economic outcomes on dairy cow health, with the aim of identifying knowledge gaps in this field of research. In total, 59 peer-reviewed articles were included using a broad range of animal health variables and economic outcomes. We found a heterogeneous body of evidence in terms of both methods, animal health measures (AHMs) and economic outcome measures used. None of the included studies makes explicit causal claims between AHMs and economic outcomes. The results suggest that common production diseases such as clinical mastitis and lameness, which are painful and affect cow health and welfare, are costly for farmers. We found a knowledge gap and lack of evidence on the impact of animal health interventions on farms' economic outcomes, as well as the long-term effects of such interventions. Future research should aim to investigate the causal links between animal health and economic outcomes.

Identification of histidine kinase inhibitors through screening of natural compounds to combat mastitis caused by Streptococcus agalactiae in dairy cattle

BACKGROUND

Mastitis poses a major threat to dairy farms globally; it results in reduced milk production, increased treatment costs, untimely compromised genetic potential, animal deaths, and economic losses. Streptococcus agalactiae is a highly virulent bacteria that cause mastitis. The administration of antibiotics for the treatment of this infection is not advised due to concerns about the emergence of antibiotic resistance and potential adverse effects on human health. Thus, there is a critical need to identify new therapeutic approaches to combat mastitis. One promising target for the development of antibacterial therapies is the transmembrane histidine kinase of bacteria, which plays a key role in signal transduction pathways, secretion systems, virulence, and antibiotic resistance.

RESULTS

In this study, we aimed to identify novel natural compounds that can inhibit transmembrane histidine kinase. To achieve this goal, we conducted a virtual screening of 224,205 natural compounds, selecting the top ten based on their lowest binding energy and favorable protein-ligand interactions. Furthermore, molecular docking of eight selected antibiotics and five histidine kinase inhibitors with transmembrane histidine kinase was performed to evaluate the binding energy with respect to top-screened natural compounds. We also analyzed the ADMET properties of these compounds to assess their drug-likeness. The top two compounds (ZINC000085569031 and ZINC000257435291) and top-screened antibiotics (Tetracycline) that demonstrated a strong binding affinity were subjected to molecular dynamics simulations (100 ns), free energy landscape, and binding free energy calculations using the MM-PBSA method.

CONCLUSION

Our results suggest that the selected natural compounds have the potential to serve as effective inhibitors of transmembrane histidine kinase and can be utilized for the development of novel antibacterial veterinary medicine for mastitis after further validation through clinical studies.

To Treat or Not to Treat: Public Attitudes on the Therapeutic Use of Antibiotics in the Dairy Industry-A Qualitative Study

This paper describes the views of 779 U.S. residents on questions related to therapeutic antibiotic use in dairy cattle. An online survey was conducted with qualitative (open-ended) questions. Respondents were offered one of three scenarios with varying degrees of information describing a farmer with a sick cow that would benefit from antibiotic therapy. The text replies to the open-ended questions were analyzed by grouping responses with similar comments and identifying patterns or themes. Content analysis showed that many of the participants in this study provided farmers with the social license to treat sick cows with antibiotics; however, some participants commented on the social license not necessarily extending to antibiotic use for growth promotion or prophylactic use. Our findings are not generalizable, but may provide some insight that should be considered when developing policies and practices regarding the use of antibiotics on dairy farms that may promote improved alignment with societal values.

Usefulness of the total and differential somatic cell count based udder health group concept for evaluating herd management practices and udder health in dairy herds

Subclinical mastitis and associated economic losses are a steady challenge in the dairy industry. The combination of the well-established somatic cell count (SCC) parameter and the new differential SCC (DSCC) opens up the possibility to categorise cows into four different udder health groups (UHG) based on results from a single milk recording/dairy herd improvement (DHI) test: UHG A: healthy/normal, ≤ 200,000 cells/mL and DSCC ≤ 65 %; B: suspicious, ≤ 200,000 cells/mL and DSCC > 65 %; C: (subclinical) mastitis, > 200,000 cells/mL and DSCC > 65 %; D: chronic/persistent mastitis, > 200,000 cells/mL and DSCC ≤ 65 %. The objectives of this study were to investigate 1) herd management practises among herds in different UHG categories and 2) herd performance parameters depending on the proportion of cows in UHG A. A total number of 41 herds in Styria, Austria, and Thuringia, Germany, were visited and interviewed for the first part of the study. The herds were categorised into 3 UHG categories depending on the proportion of cows in UHG A: I = >65 %; II = 55-65 %; and III = <55 %. Those with good udder health and best herd performance (+9 % milk yields, +11 % longevity, -35 % antibiotic treatments) applied distinct preventive measures, in particular excellent cubicle management and early antibiotic treatment (P < 0.05 each). However, preventive measures were applied to a lower extent in other herds. Herds were categorised differently using the UHG concept compared to SCC alone as the UHG-based categorisation allowed to clearer distinguish herds with medium-good from those with good udder health. A total number of 129,812 regular milk recording/DHI test day results of 890 Austrian and 183 German herds was used for the second part of the study. Results revealed a trend of increasing daily production as proportions of cows in UHG A increase. In conclusion, the UHG concept allowed clearer distinction of herds with good, medium-good, and poor udder health and could be used to promote practises leading to better animal health, less antibiotic treatments, and higher milk quality.

A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors

The decision of premature culling cows directly impacts the profitability of dairy farms. A comprehensive characterization of the primary causes of culling reasons would greatly improve both management and selection objectives in dairy cattle breeding programs. Therefore, this study aimed to analyze the temporal frequencies of 34 culling reasons in Canadian Holstein cows. After data editing and quality control, records from 3,096,872 cows culled from 9,683 herds spread across Canada were used for the analyses covering the periods from 1996 to 2020. Reproductive issues were the main culling reason accounting for 23.02%, followed by milk production (20.82%), health (20.39%), conformation problems (13.69%), economic factors (13.10%), accidents (5.67%), age-related causes (1.67%), and workability (1.63%). Nearly fifty-eight percent of cows were culled after 47 months of age. The observed frequencies of culling due to economic factors were lower than expected from 1996 to 2014 and higher than expected between 2015 and 2020. Reproduction issues had the highest culling frequencies during fall (24.54%), winter (24.02%), and spring (22.51%), while health issues were the most frequent (22.51%) culling reason in the summer season. Health issues (25.50%) and milk production (27.71%) were the most frequent culling reasons in the provinces of Quebec and Ontario, respectively. Reproductive issues showed the highest frequency across climates based on the Köppen climate classification, except for Csb (Dry-summer subtropical or Mediterranean climate) and Bsk (Middle latitude steppe climate), which correspond to small regions in Canada, where production was the most frequent culling reason (29.42% and 21.56%, respectively). Reproductive and milk performance issues were the two main culling reasons in most ecozones, except in Boreal Shield and Atlantic Marine, where health issues had the highest frequencies (25.12 and 23.75%, respectively). These results will contribute to improving management practices and selective decisions to reduce involuntary culling of Holstein cows.

Use of Danish National Somatic Cell Count Data to Assess the Need for Dry-Off Treatment in Holstein Dairy Cattle

In Denmark, PCR testing of dairy cattle is commonly used to select animals for the antibacterial treatment of intramammary infection (IMI) during the dry-off period. IMI is associated with a high somatic cell count (SCC), routinely recorded for milk quality control for most commercial dairy herds. This study aimed to compare SCC curves over the lactation among dairy cows with positive vs. negative PCR test results for four major IMI pathogens. Data from 133,877 PCR-tested Holstein cows from 1364 Danish conventional dairy herds were used to fit a nonlinear mixed-effects model using a modified four-parameter Wilmink function. We stratified the data into first, second, third or fourth and later parity and fitted Wilmink curves to all SCC observations between 6 and 305 days in milk. The PCR tests were taken before dry-off at the end of the lactation to investigate which animals qualified for selective dry cow therapy. A PCR Ct-value of 37 and below was used to determine if an animal was PCR positive for any of the following IMI pathogens: Staphylococcus aureus, Streptococcus agalactiae, Str. dysgalactiae and Str. uberis. Our findings showed that mean SCC curve fits were higher for PCR-positive animals in all four parity groups and across lactations. The use of SCC data fitted to the entire lactation for multiple lactations enabled quantification of overall differences in SCC curves between cattle with and without detected IMI, adjusted for parity group and stage of lactation. These findings are relevant to the use of SCC to support treatment decisions.

Effect of the Selective Dry Cow Therapy on Udder Health and Milk Microbiota

Recently, the use of antimicrobials on dairy farms has been significantly limited from both the legislative and consumer points of view. This study aims to check the efficacy of selective dry cow therapy (SDCT) versus blanket dry cow therapy (BDCT) on bovine udder in healthy animals. SDTC is when an antibiotic is administered only to infected cows, compared with BDCT, where all cows receive an antimicrobial, regardless of their infection status. The milk samples were collected from enrolled Holstein Friesian cows 7 days before dry-off (T0) and 10 days after calving (T1) to assess somatic cell count (SCC), intramammary infections (IMIs), and milk microbiota variation. After pre-drying sampling, cows are randomly assigned to the following treatments: internal teat sealant alone (ITS; 24 cows), which is a treatment in a cow that does not receive antibiotics in SDTC, or in combination with intramammary antibiotic treatment (A+ITS; 22 cows). Non-statistically significant results are found between the two treatment groups at T1 for SCC, milk yield, and alpha diversity in milk microbiota. A statistically (p < 0.033) T1 IMI decrease is reported in the A+ITS group, and a significant beta diversity analysis is shown between the two timepoints (p = 0.009). This study confirms the possibility of selective drying without new IMI risk or increased SCC at calving, considering healthy cows without contagious infections and SCC values >200,000 cells/mL in the previous lactation.

Scientific Productions on Precision Livestock Farming: An Overview of the Evolution and Current State of Research Based on a Bibliometric Analysis

The interest in precision livestock farming (PLF)-a concept discussed for the first time in the early 2000s-has advanced considerably in recent years due to its important role in the development of sustainable livestock production systems. However, a comprehensive bibliometric analysis of the PLF literature is lacking. To address this gap, this study analyzed documents published from 2005 to 2021, aiming to understand the historical influences on technology adoption in livestock farming, identify future global trends, and examine shifts in scientific research on this topic. By using specific search terms in the Web of Science Core Collection, 886 publications were identified and analyzed using the bibliometrix R-package. The analysis revealed that the collection consisted mostly of research articles (74.6%) and reviews (10.4%). The top three core journals were the Journal of Dairy Science, Computers and Electronics in Agriculture, and Animals. Over time, the number of publications has steadily increased, with a higher growth rate in the last five years (29.0%) compared to the initial period (13.7%). Authors and institutions from multiple countries have contributed to the literature, with the USA, the Netherlands, and Italy leading in terms of publication numbers. The analysis also highlighted the growing interest in bovine production systems, emphasizing the importance of behavioral studies in PLF tool development. Automated milking systems were identified as central drivers of innovation in the PLF sector. Emerging themes for the future included "emissions" and "mitigation", indicating a focus on environmental concerns.

Punch-excised explants of bovine mammary gland to model early immune response to infection

BACKGROUND

Mammary gland (MG) infections (mastitis) are frequent diseases of dairy cows that affect milk quality, animal welfare and farming profitability. These infections are commonly associated with the bacteria Escherichia coli and Staphylococcus aureus. Different in vitro models have been used to investigate the early response of the MG to bacteria, but the role of the teat in mastitis pathogenesis has received less attention. In this study, we used punch-excised teat tissue as an ex vivo model to study the immune mechanisms that arise early during infection when bacteria have entered the MG.

RESULTS

Cytotoxicity and microscopic analyses showed that bovine teat sinus explants have their morphology and viability preserved after 24 h of culture and respond to ex vivo stimulation with TLR-agonists and bacteria. LPS and E. coli trigger stronger inflammatory response in teat when compared to LTA and S. aureus, leading to a higher production of IL-6 and IL-8, as well as to an up-regulation of proinflammatory genes. We also demonstrated that our ex vivo model can be applied to frozen-stored explants.

CONCLUSIONS

In compliance with the 3Rs principle (replacement, reduction and refinement) in animal experimentation, ex vivo explant analyses proved to be a simple and affordable approach to study MG immune response to infection. This model, which better reproduces organ complexity than epithelial cell cultures or tissue slices, lends itself particularly well to studying the early phases of the MG immune response to infection.