Methods for Diagnosing Mastitis

Early Detection of Sub-clinical Mastitis in Murrah Buffaloes through Udder Thermogram Analysis during the Natural Progression of Infection

Mastitis is a global production disease that needs an intelligent solution to tackle effectively. Infrared Thermography (IRT) is a non-invasive technology that could be incorporated into routine day-to-day farm activities to monitor the health status of the animals. In this study, the udder health status was routinely monitored for 30 days among 41 Murrah buffaloes via IRT and the California Mastitis Test (CMT). Further, somatic cell count (SCC), microbial identification, and milk quality parameters were also estimated for representative samples. The thermal imaging data obtained was tabulated and back propagated from the 0th day to the -10th day and front propagated from the 0th day to +10th day for all the udder quarters. Results revealed that on the 0th day, the mean of udder skin surface temperature (USST) and teat skin surface temperature (TSST) showed a difference (p < 0.05) in the sub-clinical mastitis (SCM) and clinical mastitis (CM) affected quarters to the healthy quarters, and their degree of difference was the highest. The indication of infection was signaled during the -9th to -5th day to the 0th day in SCM and CM cases. There was a steep increment in the temperature from -2nd and -1st day to the 0th day of infection. Sometimes, some quarters show an increment in temperature due to mastitis during morning hours but recover by evening milking due to the animal's innate immune system. Thus, the initiation period in which the udder gets assaulted is crucial in the early assessment of SCM by monitoring temperature change using IRT.

Presence of pathogen DNA in milk harvested from quarters is associated to changes in cows' milk yield and composition

BACKGROUND

Intramammary infection is the result of invasion and multiplication of microorganisms in the mammary gland and commonly leads to mastitis in dairy animals. Although much has been done to improve cows' udder health, mastitis remains a significant and costly health issue for dairy farmers, especially if subclinical. In this study, quarter milk samples from clinically healthy cows were harvested to detect pathogens via quantitative PCR (qPCR) and evaluate changes in individual milk traits according to the number of quarters infected and the type of microorganism(s). A commercial qPCR kit was used for detection of Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis. Quarter and pooled milk information of 383 Holstein, 132 Simmental, 129 Rendena, and 112 Jersey cows in 9 Italian single-breed herds was available.

RESULTS

Among the cows with pathogen(s) present in at least 1 quarter, CNS was the most commonly detected DNA, followed by Streptococcus uberis, Mycoplasma bovis, and Streptococcus agalactiae. Cows negative to qPCR were 206 and had the lowest milk somatic cell count. Viceversa, cows with DNA isolated in ≥ 3 quarters were those with the highest somatic cell count. Moreover, when major pathogens were isolated in ≥ 3 quarters, milk had the lowest casein index and lactose content. In animals with pathogen(s) DNA isolated, the extent with whom milk yield and major solids were impaired did not significantly differ between major and minor pathogens.

CONCLUSIONS

The effect of the number of affected quarters on the pool milk quality traits was investigated in clinically healthy cows using a commercial kit. Results remark the important negative effect of subclinical udder inflammations on milk yield and quality, but more efforts should be made to investigate the presence of untargeted microorganisms, as they may be potentially dangerous for cows. For a smarter use of antimicrobials, analysis of milk via qPCR is advisable - especially in cows at dry off - to identify quarters at high risk of inflammation and thus apply a targeted/tailored treatment.

Antimicrobial resistance of Enterobacteriaceae and Staphylococcus spp. isolated from raw cow's milk from healthy, clinical and subclinical mastitis udders

Mastitis is the most common disease of dairy cattle and can be manifested in clinical and subclinical forms. The overuse of antimicrobials in the treatment and prevention of mastitis favours antimicrobial resistance and milk can be a potential route of dissemination. This study aimed to evaluate the biological quality of bulk tank milk (BTM) and the microbiological quality and signs of mastitis of freshly milked raw milk. In addition, to evaluate antimicrobial resistance in Enterobacteriaceae and Staphylococcus spp. isolated from freshly milked raw milk. None of the farms were within the official Brazilian biological quality limits for BTM. Freshly milked raw milk with signs of clinical (CMM), subclinical (SCMM) and no signs (MFM) of mastitis were detected in 6.67%, 27.62% and 65.71% samples, respectively. Most samples of freshly milked raw milk showed acceptable microbiological quality, when evaluating the indicators total coliforms (78.10%), Escherichia coli (88.57%) and Staphylococcus aureus (100%). Klebsiella oxytoca and S. aureus were the most prevalent microorganisms in SCMM and MFM samples. Antimicrobial resistance and multidrug resistance (MDR) were observed in 65.12% and 13.95% of Enterobacteriaceae and 84.31% and 5.88% of Staphylococcus spp., respectively, isolated from both SCMM and MFM samples. Enterobacteriaceae resistant to third-generation cephalosporin (3GCR) (6.98%) and carbapenems (CRE) (6.98%) and methicillin-resistant S. aureus (MRSA) (4.88%) were observed. Antimicrobial-resistant bacteria can spread resistance genes to previously susceptible bacteria. This is a problem that affects animal, human and environmental health and should be evaluated within the one-health concept.

Comparison of bacteriological culture method and multiplex real-time PCR for detection of mastitis

This study includes the evaluation of multiplex real-time PCR (rPCR) kit, which was developed to provide rapid diagnosis of mastitis infections, by working with milk samples of 2 different sources of mastitis and comparing the results with the classical bacteriological culture method (BC). A total of 273 bacteria were isolated in 226 samples (47.88%) out of 472 samples by BC. These were 139 (50.91%) Staphylococcus spp., 61 (22.34%) Streptococcus spp., 15 (5.49%) E. coli, 8 (2.93%) Enterococcus spp., 50 (18.31%) other bacteria. When we look at the multiplex rPCR results; 1052 positive were obtained for the gene regions of 14 different bacteria, 1 yeast, and 1 β-lactamase gene examined in 472 samples. While no searched gene region was found by rPCR in 78 (16.5%) of the 472 samples studied, at least 1 gene was detected in 394 (83.5%) samples. These 1052 positive samples by rPCR were; 263 (28.43%) Staphylococcus spp., 51 (5.51%) S. aureus, 57 (6.16%) Enterococcus spp., 49 (5.29%) C. bovis, 16 (1.73%) S. dysgalactiae, 84 (9.08%) S. agalactiae, 71 (7.67%) S. uberis, 73 (7.89%) E. coli, 14 (1.51%) Prototheca spp., 39 (4.21%) T. pyogenes/P. indolicus, 5 (0.54%) S. marcescens, 15 (1.62%) K. oxytoca/pneumonia, 117 (12.64%) Mycoplasma spp., 31 (3.35%) M. bovis, 40 (4.32%) yeast, and 127 samples (26.90%) were β-lactamase positive. When the antibiotic resistance of the isolates was evaluated, 78 (31.96%) tetracycline, 72 (29.5%) penicillin, and 60 (24.59%) clindamycin resistance were observed predominantly in Gram-positive isolates, while 6 (23.07%) tigecycline, 6 (23.07%) netilmicin, 6 (23.07%) pipercillin resistance was found in gram-negative isolates. While a bacteria and/or yeast gene was found by rPCR in 187 of 246 (76.01%) samples with no bacterial growth, a bacterium was isolated with BC in only 20 (8.84%) samples whose gene region was not found by rPCR. As a result, the multiplex rPCR system used in the diagnosis of mastitis has been found to be quite reliable as it can detect a large number of bacteria in a very short time compared to classical methods. Therefore, we advise the use of rPCR and/or culture for confirmation of clinical signs in mastitis and at routine mastitis surveillance.

Frequency of non-aureus staphylococci and mammaliicocci species isolated from quarter clinical mastitis: A 6-year retrospective study

Non-aureus staphylococci and mammaliicocci (NASM) are the most frequently isolated bacterial group from bovine milk samples. Most studies focus on subclinical mastitis caused by NASM; however, NASM can cause clinical mastitis (CM) as well. We evaluated retrospective data from 6 years (2017-2022) to determine the species and frequency of NASM isolated from quarter bovine CM. The data was comprised of microbiological results from quarter CM samples routinely submitted to Quality Milk Production Services at Cornell University for microbial identification by MALDI-TOF mass spectrometry. A total of 9,909 microbiological results from 410 dairy herds were evaluated. Our results showed that 29 distinct NASM species were identified, with the 8 most prevalent NASM species being Staphylococcus chromogenes, Staphylococcus haemolyticus, Staphylococcus simulans, Staphylococcus epidermidis, Staphylococcus sciuri (now Mammaliicoccus sciuri), Staphylococcus agnetis/Staphylococcus hyicus, Staphylococcus borealis, and Staphylococcus xylosus. The NASM distribution remained similar among seasons, but the frequency of NASM CM cases was higher during the summer. Our results showed different patterns of variations in the isolation frequency over time, depending on the bacterial species: increasing or decreasing trends, cyclic fluctuations, and, except for Staphylococcus borealis, a significant seasonality effect for our study's most prevalent NASM. This study showed that Staphylococcus chromogenes remains the most frequent (43%) NASM species identified from bovine CM, followed by Staphylococcus haemolyticus (18%), and Staphylococcus simulans (12%).

Interference of Streptococcus agalactiae Blitz Therapy in Staphylococcus aureus Microbiological Diagnosis in Subclinical Bovine Mastitis

Bovine mastitis is an important and costly disease to dairy cattle. Diagnostic methods usually performed in Brazil are somatic cell counts (SCC) and milk microbiology. Low bacteria shedding in milk implies no colony growth in microbiological tests and false negative results. Streptococcus agalactiae and Staphylococcus aureus are principal pathogens of mixed mastitis. However, S. agalactiae has a higher bacterial release from the mammary gland than S. aureus, affecting microbiological sensitivity to diagnose S. aureus. This study aimed to estimate the SCC and total bacterial count (TBC) from cows according to pathogen isolated in milk and to evaluate variation in S. aureus diagnosis by a microbiological test during S. agalactiae treatment, which is called blitz therapy. Both S. agalactiae and S. aureus presented high SCC means, although S. agalactiae showed shedding of bacteria 2.3 times greater than S. aureus. Microbiological sensitivity to S. aureus increased for 5 months during S. agalactiae treatment. The prevalence of S. agalactiae fell after 5 months of therapeutic procedures. The prevalence of S. aureus increased to 39.0. The results showed that due to high sensitivity, the polymerase chain reaction (PCR) could be used at the beginning of blitz therapy with the goal of S. agalactiae eradication from the dairy herd.

A Rapid and Inexpensive PCR Test for Mastitis Diagnosis Based on NGS Data

Mastitis is a common mammary gland disease of dairy cattle caused by a wide range of organisms including bacteria, fungi and algae. Mastitis contributes to economic losses of dairy farms due to reduced yield and poor quality of milk. Since the correct identification of pathogens responsible for the development of mastitis is crucial to the success of treatment, it is necessary to develop a quick and accurate test to distinguish the main pathogens causing this disease. In this paper, we describe the development of a test based on the multiplex polymerase chain reaction (PCR) method allowing for the identification of Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis and Staphylococcus aureus. When creating our test, we relied on the results from new generation sequencing (NGS) for accurate determination of species affiliation. The multiplex PCR test was verified on 100 strains including veterinary samples, ATCC and Polish Collection of Microorganisms (PCM) reference strains. The obtained results indicate that this test is accurate and displays high specificity. It may serve as a valuable molecular tool for the detection of major mastitis pathogens.

SNP Analysis of TLR4 Promoter and Its Transcriptional Factor Binding Profile in Relevance to Bovine Subclinical Mastitis

Bovine mastitis is a complex infectious disease that develops in the mammary gland, predominantly caused by a bacterial infection of mammary tissue. Genetic variability of mastitis is well established and depends upon different quantitative trait loci (QTL) related to mastitis resistance or susceptibility. The susceptibility is often attributed to single-nucleotide polymorphisms (SNPs) in the variable cow breed genomes. Several global investigative attempts have resulted in studies mapping mastitis to the variations in the relevant genes. Reports have been attributed to dramatic genetic expression changes in Toll-Like Receptor 4 (TLR4) genes in mastitis-positive cows. However, the mechanism behind this variable genetic expression of TLR4 genes has been studied poorly. The present study aims to investigate SCM through various screening tests like somatic cell count (SCC), electric conductivity (EC), pH, and California mastitis test (CMT) in milk samples. This study also aims to investigate possible mechanisms behind this variable expression of TLR4 by comparative SNP evaluation and transcriptional factor profile mining. So that the important genetic mutations and effects thereof can be exploited in selecting specific breeds with higher mastitis resistance and milk yield. Seventy Holstein Frisian (HF) crossbred dairy cows were selected in the present study. The animals were screened based on various diagnostic tests (SCC, pH, EC, and CMT). Blood samples (5 mL) were collected for extraction of DNA followed by amplification of PPR1 and PPR2 of the promoter region and 5'UTR of the bovine TLR4 gene using specific primers. Sanger's enzymatic DNA sequencing technique sequenced the amplified PCR products. Further, the identification of SNPs was done through various bioinformatic tools used in this study. The findings of the present study revealed that CMT, EC, pH, and SCC could be used for the early detection of subclinical mastitis. In the present study, a significant increase in the EC, pH, and SCC in milk samples of animals affected with SCM was found in comparison to the healthy animals. The present study also revealed 16 SNPs falling in TLR4 promoter and 5' untranslated region (5'UTR) sequences in mastitis-positive genotypes compared to reference genomes. The study also investigates the potential transcriptional factor program deployed in response to variable mastitis development resistance. In the present study, the allelic and genotype frequencies of all SNP variants in the three regions viz., PPR1, PPR2, and 5'UTR, were the same indicating the absence of heterozygous condition at the respective loci. The present study has wide applicability for researchers developing mastitis-resistant breeding programs and the data generated may aid in the selection of better genetic breeds. The transcription factor binding profiles can serve as concrete leads about the studies on bovine mastitis at the molecular level and may also aid global research groups working on transcription factor (TF)-based molecular pathology of mastitis.

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.

Electrical conductivity and total dissolved solid of raw milk for the detection of bovine subclinical mastitis

Background and Aim

Bovine subclinical mastitis (SCM) is highly prevalent among dairy cattle. A cross-sectional study was conducted in Bangladesh to evaluate the performance of electric conductivity (EC) and total dissolved solids (TDS) tests for the detection of SCM.

Materials and Methods

We randomly selected 108 milk samples from cows of different breeds in the primary milk-producing region of Pabna and Sirajgonj districts of Bangladesh. Samples were subjected to the California mastitis test (CMT), white side test (WST), electric conductivity (EC), TDS, and culture. A cow was considered positive for SCM if it tested positive in CMT, WST, and culture, whereas a cow was considered negative for SCM if it tested negative in all three methods. These gold standards have been used to evaluate the performance of the EC and TDS tests. The optimal EC and TDS cutoff values for the detection of SCM were determined using the "optimal cutoff" function in R version 4.3.1.

Results

The optimal EC cutoff value for SCM detection was found to be 6159 μS/cm or 6.16 mS/cm. A positive likelihood ratio (LR+) of 31.2 and an area under the curve (AUC) of 0.905 were obtained for this cutoff value. The optimal cutoff value for TDS was 3100 mg/L of milk, which resulted in a positive LR+ of 45.5 and an AUC of 0.924.

Conclusion

To the best of our knowledge, this is the first study to evaluate the performance of EC and TDS tests in detecting SCM in Bangladesh. These results suggest that EC and TDS tests, which are inexpensive, rapid, and easy to conduct, can effectively detect SCM at the farm level.

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.

Case-Control Study: Endogenous Procalcitonin and Protein Carbonylated Content as a Potential Biomarker of Subclinical Mastitis in Dairy Cows

Procalcitonin (PCT) and protein carbonylated content (PCC) are promising biomarkers for bacterial infection and inflammation in veterinary medicine. This study examined plasma PCT and PCC levels in healthy cows (H) and cows with subclinical mastitis (SCM). A total of 130 cows (65 H and 65 SCM) were included in this study. Blood samples were collected, and plasma was frozen at -80 °C. PCT levels were determined using a bovine procalcitonin ELISA kit, while PCC was measured following the methodology of Levine et al. Statistical analysis revealed a significant difference in PCT levels between H (75.4 pg/mL) and SCM (107.3 pg/mL) cows (p < 0.001) and significantly lower concentrations of PCC in the SCM group (H: 0.102 nmol/mL/mg, SCM: 0.046 nmol/mL/mg; p < 0.001). The PCT cut-off value for distinguishing healthy and subclinical mastitis animals was >89.8 pg/mL (AUC 0.695), with a sensitivity of 66.2% and specificity of 69.2%. PCT showed potential value as a diagnostic tool to help in decision making for subclinical mastitis cases, while PCC requires further studies to investigate the trend of this biomarker during localized pathology.

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.

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.

A sample-preparation-free, point-of-care testing system for in situ detection of bovine mastitis

We present a highly integrated point-of-care testing (POCT) device capable of immediately and accurately screening bovine mastitis infection based on somatic cell counting (SCC). The system primarily consists of a homemade cell-counting chamber and a miniature fluorescent microscope. The cell-counting chamber is pre-embedded with acridine orange (AO) in advance, which is simple and practical. And then SCC is directly identified by microscopic imaging analysis to evaluate the bovine mastitis infection. Only 4 μL of raw bovine milk is required for a simple sample testing and accurate SCC. The entire assay process from sampling to result in presentation is completed quickly within 6 min, enabling instant "sample-in and answer-out." Under laboratory conditions, we mixed bovine leukocyte suspension with whole milk and achieved a detection limit as low as 2.12 × 104 cells/mL on the system, which is capable of screening various types of clinical standards of bovine milk. The fitting degrees of the proposed POCT system with manual fluorescence microscopy were generally consistent (R2 > 0.99). As a proof of concept, four fresh milk samples were used in the test. The average accuracy of somatic cell counts was 98.0%, which was able to successfully differentiate diseased cows from healthy ones. The POCT system is user-friendly and low-cost, making it a potential tool for on-site diagnosis of bovine mastitis in resource-limited areas.

Relationship between Microflora Changes and Mammary Lipid Metabolism in Dairy Cows with Mastitis

Dairy mastitis is an inflammatory reaction caused by mechanical injury and stress within the mammary gland, during which microbial changes and abnormal lipid metabolism occur. However, the underlying mechanism is still unclear. The present study used a combination of 16S rDNA sequencing technology and lipidomics techniques to reveal the effects of mastitis on lactic microbiota and metabolites in the milk of dairy cows. Twenty multiparous Holstein dairy cows (2-3 parities) with an average body weight of 580 ± 30 kg were selected for this study. The dairy cows were allocated to control group (<5 × 104 cells /mL)) and mastitis group (>5 × 106 cells /mL) based on the somatic cell count. The results showed that mastitis caused a decrease trend in milk production (p = 0.058). The results of the 16 s sequencing indicated a significant decrease (p < 0.05) in the number of Proteobacteria, Tenericutes colonized in mastitis milk, and the number of Firmicutes, Bacteroidetes and Actinobacteria communities increased significantly (p < 0.05). The lipidomics results revealed that the changes in lipid content in mastitis milk were correlated with arachidonic acid metabolism, α -linolenic acid metabolism and glycerol phospholipid metabolism. The results showed that mastitis may cause abnormal lipid metabolism in milk by regulating the diversity of milk microflora, and ultimately affect the milk quality.

Bacterial culture and antimicrobial susceptibility results from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia from 2015 to 2019

A 5-year retrospective study was conducted to describe the mastitis-causing organisms isolated from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia. The aim of this study was to identify temporal, geographical, and seasonal patterns of occurrence for the organisms and report the in vitro susceptibility of the most common mastitis-causing pathogens. In total, 22,102 milk samples were submitted between 2015 and 2019. The results were reported as positive growth for at least one significant organism (n = 11,407; 51.6%), no growth (n = 5,782; 26.2%), and mixed/contaminated growth (n = 4,913; 22.2%). Culture results for no growth, gram-negative bacteria, and eukaryotic organisms were combined for each region, and they were accounted for between 23 and 46% of submissions. These results represent a subset of mastitis cases for which the antibiotic treatment may not be warranted. A total of 11,907 isolates were cultured from 11,407 milk samples. The most common isolated organisms were Streptococcus uberis [41.3%; 95% confidence interval (CI): 40.4-42.1%] and Staphylococcus aureus (23.6%; 95% CI: 22.8-24.3%). For S. uberis and S. aureus, there was an association between a positive culture result and the dairy region. All regions except for the Sub-tropical Dairy region were more likely to culture S. uberis compared to the reference, Dairy NSW (P < 0.001). Similarly, for S. aureus, a positive culture result was more likely in all other dairy regions compared to Dairy NSW (P < 0.001). The LISA cluster analysis identified differences between High-High (hotspot) postcodes for S. aureus and S. uberis throughout all the analyzed dairy regions. These results highlight the need for further investigations into specific risk factors, such as environmental factors and herd-level predictors, which may have influenced the observed regional variations. Common mastitis-causing pathogens showed overall good susceptibility to a range of antimicrobials used in the treatment of mastitis. On-going surveillance of mastitis-causing pathogens and their antimicrobial susceptibilities will facilitate targeted mastitis control and treatment programs.

Mastitis in Dairy Cattle: On-Farm Diagnostics and Future Perspectives

Mastitis is one of the most important diseases in dairy cattle farms, and it can affect the health status of the udder and the quantity and quality of milk yielded. The correct management of mastitis is based both on preventive and treatment action. With the increasing concern for antimicrobial resistance, it is strongly recommended to treat only the mammary quarters presenting intramammary infection. For this reason, a timely and accurate diagnosis is fundamental. The possibility to detect and characterize mastitis directly on farm would be very useful to choose the correct management protocol. Some on-field diagnostic tools are already routinely applied to detect mastitis, such as the California Mastitis Test and on-farm culture. Other instruments are emerging to perform a timely diagnosis and to characterize mastitis, such as Infra-Red Thermography, mammary ultrasound evaluation and blood gas analysis, even if their application still needs to be improved. The main purpose of this article is to present an overview of the methods currently used to control, detect, and characterize mastitis in dairy cows, in order to perform a timely diagnosis and to choose the most appropriate management protocol, with a specific focus on on-farm diagnostic tools.

Pathogen Detection via Quantitative PCR in Milk of Healthy Cows Collected Using Different Sampling Protocols

In this study we evaluated the prevalence of pathogens detected via quantitative PCR (qPCR) in milk from apparently healthy cows to identify the most common etiological agents present in Italian dairy farms. Milk samples were collected using a sterile protocol at quarter-level (3239 samples, 822 cows) and a conventional protocol at udder level as composite milk from the functional quarters of each cow (5464 samples, 5464 cows). The qPCR commercial kit detected Mycoplasma bovis, Mycoplasma spp., Staphylococcus aureus, coagulase-negative staphylococci (CNS), Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Prototheca spp., Escherichia coli, Klebsiella spp., Enterococcus spp. and Lactococcus lactis ssp. lactis as well as DNA from the penicillin resistance β-lactamase gene from staphylococci. The prevalence of specific DNA was calculated based on its presence or absence in the samples, factoring in both the sampling protocols and herds. Regardless of the sampling protocol used, the most frequently detected pathogens were CNS (26.6% in sterile and 13.9% in conventional protocol) and Streptococcus uberis (9.6% and 16.5%, respectively). These results underscore the necessity for pathogen-specific interventions at the farm level to enhance the udder health of dairy cows via management recommendations.

Advances in Diagnostic Approaches and Therapeutic Management in Bovine Mastitis

Mastitis causes huge economic losses to dairy farmers worldwide, which largely negatively affects the quality and quantity of milk. Mastitis decreases overall milk production, degrades milk quality, increases milk losses because of milk being discarded, and increases overall production costs due to higher treatment and labour costs and premature culling. This review article discusses mastitis with respect to its clinical epidemiology, the pathogens involved, economic losses, and basic and advanced diagnostic tools that have been used in recent times to diagnose mastitis effectively. There is an increasing focus on the application of novel therapeutic approaches as an alternative to conventional antibiotic therapy because of the decreasing effectiveness of antibiotics, emergence of antibiotic-resistant bacteria, issue of antibiotic residues in the food chain, food safety issues, and environmental impacts. This article also discussed nanoparticles'/chitosan's roles in antibiotic-resistant strains and ethno-veterinary practices for mastitis treatment in dairy cattle.

Evaluation of Cow-Side Meters to Determine Somatic Cell Count in Individual Cow Quarter and Bulk-Tank Milk Samples

Intramammary infections, which cause mastitis, can increase treatment and labor costs, decrease milk production, and affect milk quality. Meters that measure quarter somatic cell count (SCC) could be used to make more informed dry cow therapy decisions. The objective of this study was to compare the RT-10 iPhone adapter (RT-10; Dairy Quality Inc., Newmarket, ON, Canada), DeLaval Cell Counter (DSCC; DeLaval, Gurnee, IL, USA), Porta Check Quick Test (PortaCheck, White City, OR, USA), California Mastitis Test (ImmuCell, Portland, ME USA), pH meter (Hanna Instruments, Smithfield, RI, USA), electrical conductivity meter (OHAUS, Parsippany, NJ, USA), and the dual laser infrared temperature thermometer (Klein Tools, Lincolnshire, IL, USA) for measuring SCC in individual Holstein mammary quarters in comparison to a reference standard, the Fourier Transform Spectrometer 600 Combi System (Combi; Bentley Instruments, Chaska, MN, USA). Meters were evaluated using 658 individual cow quarter samples and 100 bulk-tank samples to measure SCC. Individual quarter milk samples from 160 cows from four commercial dairy herds were collected just before dry off and tested within 4 h of collection. To test bulk-tank SCC, 100 bulk-tank milk samples (25 mL) were collected from UC Davis Veterinary Medicine Teaching and Research Milk Quality Lab. Meter SCC values were regressed on observed Combi SCC. Goodness of fit was then evaluated by partitioning the mean square predicted error (MSPE). For individual quarter SCC, RT-10 had the highest coefficient of determination (R² = 0.86), lowest MSPE, and highest proportion of MSPE due to random variation (96%). Both the RT-10 and DSCC had the highest sensitivity and specificity for identifying quarter SCC above and below 200,000 cells/mL. For bulk-tank SCC, DSCC had the highest coefficient of determination (R² = 0.45), lowest MSPE, and highest proportion of MSPE due to random variation (80%). The RT-10 and DSCC could be used to measure individual quarter SCC to determine which cows to treat at dry off potentially reducing antibiotic use.

Status of udder health performance indicators and implementation of on farm monitoring on German dairy cow farms: results from a large scale cross-sectional study

Regional benchmarking data enables farmers to compare their animal health situation to that of other herds and identify areas with improvement potential. For the udder health status of German dairy cow farms, such data were incomplete. Therefore, the aim of this study was (1) to describe the incidence of clinical mastitis (CM), (2) to describe cell count based udder health indicators [annual mean test day average of the proportion of animals without indication of mastitis (aWIM), new infection risk during lactation (aNIR), and proportion of cows with low chance of cure (aLCC); heifer mastitis rate (HM)] and their seasonal variation, and (3) to evaluate the level of implementation of selected measures of mastitis monitoring. Herds in three German regions (North: n = 253; East: n = 252, South: n = 260) with different production conditions were visited. Data on CM incidence and measures of mastitis monitoring were collected via structured questionnaire-based interviews. Additionally, dairy herd improvement (DHI) test day data from the 365 days preceding the interview were obtained. The median (Q0.1, Q0.9) farmer reported incidence of mild CM was 14.8% (3.5, 30.8%) in North, 16.2% (1.9, 50.4%) in East, and 11.8% (0.0, 30.7%) in South. For severe CM the reported incidence was 4.0% (0.0, 12.2%), 2.0% (0.0, 10.8%), and 2.6% (0.0, 11.0%) for North, East, and South, respectively. The median aWIM was 60.7% (53.4, 68.1%), 59.0% (49.7, 65.4%), and 60.2% (51.5, 67.8%), whereas the median aNIR was 17.1% (13.6, 21.6%), 19.9% (16.2, 24.9%), and 18.3% (14.4, 22.0%) in North, East, and South, respectively with large seasonal variations. Median aLCC was ≤1.1% (≤ 0.7%, ≤ 1.8%) in all regions and HM was 28.4% (19.7, 37.2%), 35.7% (26.7, 44.2%), and 23.5% (13.1, 35.9%), in North, East and South, respectively. Participation in a DHI testing program (N: 95.7%, E: 98.8%, S: 89.2%) and premilking (N: 91.1%, E: 93.7%, S: 90.2%) were widely used. Several aspects of udder health monitoring, including exact documentation of CM cases, regular microbiological analysis of milk samples and the use of a veterinary herd health consultancy service were not applied on many farms. The results of this study can be used by dairy farmers and their advisors as benchmarks for the assessment of the udder health situation in their herds.

Current and Emerging Diagnostic Approaches to Bacterial Diseases of Ruminants

The diagnostic approaches and methods to detect bacterial pathogens in ruminants are discussed, with a focus on cattle. Conventional diagnostic methods using culture, isolation, and characterization are being replaced or supplemented with new methods. These include molecular diagnostics such as real-time polymerase chain reaction and whole-genome sequencing. In addition, methods such as matrix-assisted laser desorption ionization-time-of-flight mass spectrometry enable rapid identification and enhanced pathogen characterization. These emerging diagnostic tools can greatly enhance the ability to detect and characterize pathogens, but performance and interpretation vary greatly across sample and pathogen types, disease syndromes, assay performance, and other factors.

Immunological and Oxidative Biomarkers in Bovine Serum from Healthy, Clinical, and Sub-Clinical Mastitis Caused by Escherichia coli and Staphylococcus aureus Infection

The study aimed to investigate the mastitis' emerging causative agents and their antimicrobial sensitivity, in addition to the hematological, biochemical indicators, oxidative biomarkers, acute phase protein (APP), and inflammatory cytokine changes in dairy farms in Gamasa, Dakahlia Governorate, Egypt. One hundred Holstein Friesian dairy cattle with clinical and subclinical mastitis were investigated and were allocated into three groups based on a thorough clinical examination. Escherichia coli and Staphylococcus aureus were found responsible for the clinical and subclinical mastitis in dairy farms, respectively. Multiple drug resistance (MDR) was detected in 100%, and 94.74% of E. coli and S. aureus isolates, respectively. Significantly low RBCs count, Hb, and PCV values were detected in mastitic cows compared with both subclinical mastitic and control groups; moreover, WBCs, lymphocytes, and neutrophil counts were significantly diminished in mastitic cows compared to the controls. Significantly higher levels of AST, LDH, total protein, and globulin were noticed in both mastitic and subclinical mastitic cows. The haptoglobin, fibrinogen, amyloid A, ceruloplasmin, TNF-α, IL-1β, and IL-6 levels were statistically increased in mastitic cows compared to the controls. Higher MDA levels and reduction of TAC and catalase were identified in all the mastitic cases compared to the controls. Overall, the findings suggested potential public health hazards due to antimicrobial resistance emergence. Meanwhile, the APP and cytokines, along with antioxidant markers can be used as early indicators of mastitis.

Characterization of mammary pathogenic Escherichia coli reveals the diversity of Escherichia coli isolates associated with bovine clinical mastitis in Brazil

Mammary pathogenic Escherichia coli (MPEC) is one of the most common pathogens associated with clinical mastitis. We analyzed isolates obtained from milk samples of cows with clinical mastitis, collected from 10 farms in Brazil, to verify molecular and phenotypic characteristics. A total of 192 (4.5%) mammary pathogenic E. coli isolates were obtained from 4,275 milk samples analyzed, but we tested 161. We assigned most of these isolates to E. coli phylogroups B1 (52.8%) and A (36.6%), although phylogroups B2, C, D, E, and unknown also occurred. All isolates were assessed for the presence of several genes encoding virulence factors, such as adhesins (sfaDE, papC, afaBC III, ecpA, fimH, papA, and iha), toxins (hlyA, cnf1, sat, vat, and cdt), siderophores (iroN, irp2, iucD, ireA, and sitA), an invasion protein (ibeA), and serum resistance proteins (traT, KpsMTII, and ompT), and isolates from phylogroups B1, B2, and E showed up to 8 genes. Two isolates harbored the locus of enterocyte effacement (escN⁺) and lack the bundle-forming pilus (bfpB^-) operon, which corresponds to a molecular profile of a subgroup of diarrheagenic E. coli (aEPEC), thus being classified as hybrid MPEC/aEPEC isolates. These isolates displayed a localized adherence-like pattern of adherence in HeLa cells and were able to promote F-actin polymerization underneath adherent bacteria. Based on the pulsed-field gel electrophoresis analyses, considerable genetic variability was observed. A low index of antimicrobial resistance was observed and 2 extended-spectrum β-lactamase-producing E. coli were identified, both harboring bla_CTX-M15 gene, and were classified as ST10 and ST993 using multilocus sequence typing. A total of 148 (91.2%) isolates were weak biofilm producers or formed no biofilm. Because raw milk is still frequently consumed in Brazil, the occurrence of virulence factor-encoding genes from extraintestinal or diarrheagenic E. coli added to the presence of extended-spectrum β-lactamase-producing isolates can turn this veterinary medicine problem into a public health concern.

The effect of antibiotic versus no treatment at dry-off on udder health and milk yield in subsequent lactation: A retrospective analysis of Austrian health recording data from dairy herds

Bovine mastitis is the most commonly diagnosed disease of dairy cows worldwide and causes extensive economic losses to milk producers. Intramammary infection status before dry-off plays a decisive role with respect to udder health and milk yield in the subsequent lactation. The aim of this study was to compare the effect of antibiotic dry cow therapy (DCT) versus no treatment at dry-off on milk yield, somatic cell count (SCC), inflammation of the mammary gland (IMG), and the incidence of clinical mastitis in the subsequent lactation. Dairy herd data from 251 Austrian dairy farms were recorded over an observation period of 12 mo and subsequently analyzed. The data set included 5,018 dairy cows: 2,078 were treated with antibiotics (abDCT group) and 2,940 were not treated (noDCT group) at dry-off. The abDCT group was subdivided, based on the antimicrobial active substances used for drying off, into 4 different groups (penicillins, cloxacillin, cephalosporins, and rifaximin). Based on bacteriological culture results, infections were grouped into those caused by major, minor, and other pathogens. Additionally, the IMG was defined via SCC from milk recording data using a cutoff of 200,000 cells/mL before drying off and after calving. The incidence of clinical mastitis cases within 30 and 90 d in milk was calculated using veterinary diagnosis data. To investigate the effect of different dry cow therapies on the following parameters: milk yield, SCC, and diagnosed clinical mastitis cases, different linear mixed models were constructed. Overall, the abDCT group was determined to have a significantly higher milk yield over 305 d in milk in the subsequent lactation (increase of 6.18%), compared with the noDCT group (increase of 4.29%). Both groups (abDCT and noDCT) demonstrated a decrease in the first SCC after calving compared with the SCC before dry-off, although the treated cows had a significantly higher reduction. Regarding the different antibiotic groups, with exception of the rifaximin treated cows, all antibiotic groups showed a significant difference from not treated cows with respect to SCC. Additionally, we were able to demonstrate that cows with IMG before dry-off had a 2.073 times higher chance of an increased SCC (>200,000 cells/mL) after calving. With respect to the veterinary diagnosis data, neither the IMG before drying off nor the type of DCT had a significant influence on the probability of developing clinical mastitis within 30 or 90 d in milk. Only a small number of treatments was accompanied with a bacteriological examination before drying off. However, the existing data in this study indicates that the intramammary infection status before dry-off in combination with different dry cow treatments influences udder health and milk yield after calving. Nevertheless, further studies with larger data sets of bacteriological examinations are necessary to enable a more in-depth investigation into the effects of different antibiotic substances used for DCT.

Effect of somatic cell count on milk composition and some chemical properties of milk

ABSTRACT Subclinical mastitis is a very important disease for dairy cattle farms. As a result of the deterioration of milk quality, it causes economic losses in enterprises. Milk samples of 180 cows were divided into five groups according to the somatic cell count. Some chemical properties and composition were measured in milk samples. The ratio of solid-non-fat, mineral matter, lactose, and protein decreased as the somatic cell count of the milk increased (P˂0.05). No statistical difference was observed between the fat content of milk and the level of somatic cell count (P˃0.05). Although specific gravity decreases (P˂0.05), the electrical conductivity increases (P˂0.001) in milk with high levels of somatic cell count. The milk quality of dairy cattle deteriorates due to the high somatic cell count. Therefore, regular monitoring of somatic cell count is recommended in dairy farms to monitor changes in fat, protein, solid-non-fat, lactose, and mineral matter ratios as well as some chemical properties that make up the milk composition.

MALDI-TOF mass spectrometry profiling of bovine skim milk for subclinical mastitis detection

Introduction

Mastitis is one of most impacting health issues in bovine dairy farming that reduces milk yield and quality, leading to important economic losses. Subclinical forms of the disease are routinely monitored through the measurement of somatic cell count (SCC) and microbiological tests. However, their identification can be tricky, reducing the possibilities of early treatments. In this study, a MALDI-TOF mass spectrometry approach was applied to milk samples collected from cows classified according to the SCC, to identify differences in polypeptide/protein profiles.

Materials and methods

Twenty-nine raw milk samples with SCC &gt;200,000 cell/ml (group H) and 91 samples with SCC lower than 200,000 (group L) were randomly collected from 12 dairy farms. Spectral profiles from skim milk were acquired in the positive linear mode within the 4,000–20,000 m/z mass acquisition range.

Results and discussion

Based on signal intensity, a total of 24 peaks emerged as significant different between the two groups. The most discriminant signals (4,218.2 and 4,342.98 m/z) presented a ROC curve with AUC values higher than 0.8. Classification algorithms (i.e., quick classifier, genetic algorithm, and supervised neural network) were applied for generating models able to classify new spectra (i.e., samples) into the two classes. Our results support the MALDI-TOF mass spectrometry profiling as a tool to detect mastitic milk samples and to potentially discover biomarkers of the disease. Thanks to its rapidity and low-cost, such method could be associated with the SCC measurement for the early diagnosis of subclinical mastitis.

Genetic and Antimicrobial Resistance Profiles of Mammary Pathogenic E. coli (MPEC) Isolates from Bovine Clinical Mastitis

Mammary pathogenic E. coli (MPEC) is one of the main pathogens of environmental origin responsible for causing clinical mastitis worldwide. Even though E. coli are strongly associated with transient or persistent mastitis and the economic impacts of this disease, the virulence factors involved in the pathogenesis of MPEC remain unknown. Our aim was to characterize 110 MPEC isolates obtained from the milk of cows with clinical mastitis, regarding the virulence factor-encoding genes present, adherence patterns on HeLa cells, and antimicrobial resistance profile. The MPEC isolates were classified mainly in phylogroups A (50.9%) and B1 (38.2%). None of the isolates harbored genes used for diarrheagenic E. coli classification, but 26 (23.6%) and 4 (3.6%) isolates produced the aggregative or diffuse adherence pattern, respectively. Among the 22 genes investigated, encoding virulence factors associated with extraintestinal pathogenic E. coli pathogenesis, fimH (93.6%) was the most frequent, followed by traT (77.3%) and ompT (68.2%). Pulsed-field gel electrophoresis analysis revealed six pulse-types with isolates obtained over time, thus indicating persistent intramammary infections. The genes encoding beta-lactamases detected were as follows: bla_TEM (35/31.8%); bla_CTX-M-2/bla_CTX-M-8 (2/1.8%); bla_CTX-M-15 and bla_CMY-2 (1/0.9%); five isolates were classified as extended spectrum beta-lactamase (ESBL) producers. As far as we know, papA, shf, ireA, sat and bla_CTX-M-8 were detected for the first time in MPEC. In summary, the genetic profile of the MPEC studied was highly heterogeneous, making it impossible to establish a common genetic profile useful for molecular MPEC classification. Moreover, the detection of ESBL-producing isolates is a serious public health concern.

Diagnosing Intramammary Infection: Meta-Analysis and Mapping Review on Frequency and Udder Health Relevance of Microorganism Species Isolated from Bovine Milk Samples

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry provides accurate species-level identification of many, microorganisms retrieved from bovine milk samples. However, not all those microorganisms are pathogenic. Our study aimed to: (1) determine the species-specific prevalence of microorganisms identified in bovine milk of apparently healthy lactating quarters vs. quarters with clinical mastitis (CM); and (2) map current information and knowledge gaps on udder health relevance of microorganisms retrieved from bovine milk samples. A mixed study design (meta-analysis and mapping review) was chosen. We gathered several large Canadian, US and Brazilian data sets of MALDI-TOF results for organisms cultured from quarter milk samples. For meta-analysis, two datasets (apparently healthy quarters vs. CM samples) were organized. A series of meta-analyses was conducted to determine microorganisms' prevalence. Then, each species reported was searched through PubMed to investigate whether inflammation (increased somatic cell count (SCC) or signs of CM) was associated with microorganism's recovery from milk. A total of 294 different species of microorganisms recovered from milk samples were identified. Among 50,429 quarter-milk samples from apparently healthy quarters, the 5 most frequent species were Staphylococcus chromogenes (6.7%, 95% CI 4.5-9.2%), Aerococcus viridans (1.6%, 95% CI 0.4-3.5%), Staphylococcus aureus (1.5%, 95% CI 0.5-2.8%), Staphylococcus haemolyticus (0.9%, 95% CI 0.4-1.5%), and Staphylococcus epidermidis (0.7%, 95% CI 0.2-1.6%). Among the 43,924 quarter-milk CM samples, the 5 most frequent species were Escherichia coli (11%, 95% CI 8.1-14.3%), Streptococcus uberis (8.5%, 95% CI 5.3-12.2%), Streptococcus dysgalactiae (7.8%, 95% CI 4.9-11.5%), Staphylococcus aureus (7.8%, 95% CI 4.4-11.9%), and Klebsiella pneumoniae (5.6%, 95% CI 3.4-8.2%). When conducting the PubMed literature search, there were 206 species identified by MALDI-TOF for which we were not able to find any information regarding their association with CM or SCC. Some of them, however, were frequently isolated in our multi-country dataset from the milk of quarters with CM (e.g., Citrobacter koseri, Enterococcus saccharolyticus, Streptococcus gallolyticus). Our study provides guidance to veterinarians for interpretation of milk bacteriology results obtained using MALDI-TOF and identifies knowledge gaps for future research.

Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers

Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.

Identification of Changes in Rumination Behavior Registered with an Online Sensor System in Cows with Subclinical Mastitis

The aim of the present study is to determine the relationship between subclinical mastitis and rumination behavior registered with an online sensor system. Based on the findings of the general clinical examination of 650 milking cows, 10 cows with subclinical mastitis (SCM) and 10 clinically healthy cows (HG) were selected (without clinical signs of any diseases). Rumination behavior biomarkers were registered with RumiWatch noseband sensors (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Sensors were implanted on the first day after calving. Data from the RWS 13 days before diagnosis of SCM and 13 days after diagnosis of SCM were compared with HG data from the same period. Healthy cows were checked alongside SCM cows on the same days. In our study, we found that healthy cows spent more time engaging in rumination and drinking (p < 0.05) and also had more boluses per rumination. Moreover, among cows with subclinical mastitis, rumination time from day 4 to day 0 decreased by 60.91%, drinking time decreased by 48.47%, and the number of boluses per rumination decreased by 8.67% (p < 0.05). The results indicate that subclinical affects time and rumination chews registered with sensor systems. However, additional studies with larger numbers of animals are required to confirm these results. Furthermore, the impact of heat stress, estrus, and other effects on rumination behavior biomarkers should be evaluated.

The successful use of -omic technologies to achieve the 'One Health' concept in meat producing animals

Human health and wellbeing are closely linked to healthy domestic animals, a vital wildlife, and an intact ecosystem. This holistic concept is referred to as 'One Health'. In this review, we provide an overview of the potential and the challenges for the use of modern -omics technologies, especially transcriptomics and proteomics, to implement the 'One Health' idea for food-producing animals. These high-throughput studies offer opportunities to find new potential molecular biomarkers to monitor animal health, detect pharmacological interventions and evaluate the wellbeing of farm animals in modern intensive livestock systems.

Escherichia coli Mastitis in Dairy Cattle: Etiology, Diagnosis, and Treatment Challenges

Bovine mastitis is an inflammation of the udder tissue parenchyma that causes pathological changes in the glandular tissue and abnormalities in milk leading to significant economic losses to the dairy industry across the world. Mammary pathogenic Escherichia (E.) coli (MPEC) is one of the main etiologic agents of acute clinical mastitis in dairy cattle. MPEC strains have virulence attributes to resist the host innate defenses and thrive in the mammary gland environment. The association between specific virulence factors of MPEC with the severity of mastitis in cattle is not fully understood. Furthermore, the indiscriminate use of antibiotics to treat mastitis has resulted in antimicrobial resistance to all major antibiotic classes in MPEC. A thorough understanding of MPEC’s pathogenesis and antimicrobial susceptibility pattern is required to develop better interventions to reduce mastitis incidence and prevalence in cattle and the environment. This review compiles important information on mastitis caused by MPEC (e.g., types of mastitis, host immune response, diagnosis, treatment, and control of the disease) as well as the current knowledge on MPEC virulence factors, antimicrobial resistance, and the dilemma of MPEC as a new pathotype. The information provided in this review is critical to identifying gaps in knowledge that will guide future studies to better design diagnostic, prevent, and develop therapeutic interventions for this significant dairy disease.

Advantages and Challenges of Differential Immune Cell Count Determination in Blood and Milk for Monitoring the Health and Well-Being of Dairy Cows

A key challenge of the 21st century will be to provide the growing world population with a sustainable and secure supply of food. Consequently, the dairy farming’s primary task is to lower milk losses and other inefficiencies associated with diseased cows. Moreover, a shift from curative to preventive health management would be desirable for mastitis and a wide variety of other infectious and non-infectious cattle diseases, some of which are known to have profound negative effects on the performance and well-being of cows. Differential cell counting (DCC), a procedure that aims to determine the proportions of different somatic cell types in raw milk samples, has not only the potential to optimize mastitis diagnostics, but it could furthermore serve as a diagnostic tool for monitoring the general and overall health status of dairy cows. Based on a broad search of the literature, the practical utility of various types of DCC is summarized and discussed in this review. Since it might be of advantage to interpret DCC with the aid of data from studies in humans, differences between the immune systems of humans and dairy cattle, with a special focus on surface marker expression profiles and γδ (gamma delta) T-cell characteristics, are also described.

Using High-Resolution Differential Cell Counts (HRDCCs) in Bovine Milk and Blood to Monitor the Immune Status over the Entire Lactation Period

Differential cell counts in milk offer a deeper insight into the immunology of the mammary gland and might even provide information about the systemic health status of a dairy cow. Consequently, their potential as a diagnostic method to identify biomarkers has been a subject of research for quite some time. The objective of our study was to closely monitor the immune status of eight healthy dairy cows throughout their whole lactation. For this, high-resolution differential cell counts in milk and blood were determined by means of flow cytometry, which included 10 subpopulations of the 3 main populations of immune cells and their viability. Milk and blood samples were taken twice a week in the first 100 days after calving and once a week during the remaining lactation period: in total, 55 (52–57) blood and 55 (52–57) milk samples per animal. In addition, six well-established routine laboratory biomarkers, i.e., haptoglobin, calcium, and different metabolic parameters (non-esterified fatty acids, β-hydroxybutyric acid, bilirubin, and glutamate dehydrogenase), were analyzed in all blood samples. Furthermore, a standard differential blood cell count was performed on all blood samples. We found substantial differences between cell count progressions in the blood and milk. The distribution of cell populations in the blood remained mostly stable throughout the lactation, albeit at different individual levels. Several cell populations in the milk showed a noticeable dynamic over time, which caused a separation of different lactation stages in clustering analyses. Gamma delta T cells and CD4+ T cells in the milk stood out as they showed characteristic fluctuations during the course of lactation as well as minor changes in the case of inflammation. The determination of a differential cell count has the potential to be a sensitive diagnostic and prognostic tool in bovine milk. Further studies need to show to what extent the method is suitable for routine diagnostics and how to deal with animal-specific differences.

First test-day postcalving risk factors for clinical mastitis in southern Chile dairy farms: A retrospective cohort study

We conducted a retrospective cohort study to evaluate risk factors associated with clinical mastitis in dairy cows in southern Chile between the first milk test after calving to 200 d in milk (DIM). Data from 8,772 cows were collected from June 2017 to November 2019 on 10 dairy farms selected by convenience in southern Chile. Data were analyzed using a multivariable mixed logistic regression using a manual backward selection process with logit link function and farm as a random effect. The dependent variable was clinical mastitis between the first milking sample collected by monthly milk sampling program up to 200 DIM. Days in milk, fat, urea, parity, season, and somatic cell counts were statistically associated with clinical mastitis in the first 200 d in milk. Cows with higher than average milk yield, parity, urea, and somatic cell count were at greater odds of being diagnosed with clinical mastitis compared with their respective referents. In contrast, higher milk fat was associated with lower odds of clinical mastitis. Significant interactions between days in milk with season and parity were observed, where for every 5-d increase in DIM, the odds of clinical mastitis decreased by different proportions depending on the interaction. Identified risk factors for clinical mastitis using first monthly milk sampling data can help dairy farmers in Chile implement herd-level mastitis prevention and control measures.

Mastitis Control and Intramammary Antimicrobial Stewardship in Ireland: Challenges and Opportunities

The Veterinary Medicines Regulation (EU 2019/6) came into force in all EU member states on 28 January 2022. This regulation places particular emphasis on prudent and responsible antimicrobial use in food animal production. Key changes include restrictions on the prophylactic use of antimicrobials in animals, and the possibility to reserve certain antimicrobials for humans only. The Regulation presents challenges to the Irish dairy industry, particularly with respect to current approaches to dry cow therapy. In response, the CellCheck technical working group (TWG, a technical group working in support of CellCheck, the national mastitis control programme) have developed pragmatic national and farm-level recommendations in support of improved mastitis control and intramammary antimicrobial stewardship in the Irish dairy industry. This paper outlines these recommendations, and provides an overview of the evidence considered to inform the TWG during its work (including the Regulation, policy perspectives, international best-practice, international scientific reviews and specific Irish challenges). In many key areas of concern, the TWG recognises the challenges in seeking to shape recommendations in the absence of robust and practical scientific evidence. For this reason, some of the recommended actions are pragmatic in nature, informed by national and international experiences. Periodic programme review will be needed, informed by ongoing monitoring of key performance indicators, to identify those actions that are most effective in an Irish context.

Combating Bovine Mastitis in the Dairy Sector in an Era of Antimicrobial Resistance: Ethno-veterinary Medicinal Option as a Viable Alternative Approach

Bovine mastitis (BM) is the traditional infectious condition in reared cattle which may result in serious repercussions ranging from animal welfare to economic issues. Owing to the high costs associated with preventative practices and therapeutic measures, lower milk output, and early culling, bovine mastitis is accountable for most of the financial losses suffered in cattle farming. Streptococcus agalactiae, Staphylococcus aureus, Streptococcus dysgalactiae and coliform bacteria are the predominant pathogens for bovine mastitis. In addition, the occurrence of BM has been linked to lactation stage and poor management, in the latter case, the poor stabling conditions around udder hygiene. BM occurs throughout the world, with varying rates of Streptococcus agalactiae infection in different regions. Despite the modern techniques, such as the appropriate milking practices that are applied, lower levels of pathogen vulnerability may help to prevent the development of the disease, BM treatment is primarily reliant on antibiotics for both prophylactic and therapeutic purposes. Nevertheless, as a result of the proliferation of bacterial agents to withstand the antibiotic effects, these therapies have frequently proven ineffectual, resulting in persistent BM. Consequently, alternative medicines for the management of udder inflammation have been researched, notably natural compounds derived from plants. This review focuses on BM in terms of its risk factors, pathogenesis, management, the molecular identification of causative agents, as well as the application of ethno-veterinary medicine as an alternative therapy.

MiRNAs in milk can be used towards early prediction of mammary gland inflammation in cattle

Considering the importance of early disease detection for reducing the huge financial and animal welfare impact of bovine mastitis globally, improved tools are urgently needed that can accurately detect early mammary inflammation. MiRNAs have demonstrated value as disease biomarkers, however, their potential for accurately detecting early mammary inflammation has not been examined in detail. To address this, we investigated the association between levels of four inflammation-associated miRNAs (bta-miR-26a, bta-miR-142-5p, bta-miR-146a and bta-miR-223) and CMT scores (0 to 3) obtained from a large number of individual quarter milk samples (n = 236) collected from dairy cows at different lactations (1 to 4). Initial analyses (n = 21 samples) confirmed that the levels of each of bta-miR-142-5p, bta-miR-146a and bta-miR-223 in whole milk were significantly correlated with mRNA levels of known inflammatory markers (HP, TNF, CXCL8 and IL1B) in milk cells (Rho ≥ 0.49, P < 0.005). Subsequent analyses (n = 215 samples) revealed a significant effect of CMT score on each of the four miRNAs analysed (P < 0.0001), characterised by a progressive increase in miRNA levels in milk as CMT score increase from 0 to > 1. Moreover, a significant effect of lactation number (P < 0.01) for bta-miR-26a, bta-miR-142-5p and bta-miR-146a was attributed to higher miRNA levels during lactation 1 than later lactations. Finally, by generating ROC curves we showed that bta-miR-223 and bta-miR-142-5p levels could identify early inflammatory changes in individual quarter milk samples (CMT1) with high accuracy (100% sensitivity, > 81% specificity). Our results provide novel proof of the value of miRNAs as early diagnostic biomarkers of bovine mastitis.

Frequently used therapeutic antimicrobials and their resistance patterns on Staphylococcus aureus and Escherichia coli in mastitis affected lactating cows

Mastitis is one of the most frequent and costly production diseases of dairy cattle. It is frequently treated with broad-spectrum antimicrobials. The objectives of this work were to investigate the prevalence of Staphylococcus aureus and Escherichia coli, find out the antimicrobials used in mastitis treatment, and explore the antimicrobial resistance profile including detection of resistance genes. Bacterial species and antimicrobial resistance genes were confirmed by the polymerase-chain reaction. A total of 450 cows were screened, where 23 (5.11%) and 173 (38.44%) were affected with clinical and sub-clinical mastitis, respectively. The prevalence of S. aureus was 39.13% (n = 9) and 47.97%(n = 83) while, E. coli was 30.43% (n = 7) and 15.60% (n = 27) in clinical and sub-clinical mastitis affected cows, respectively. The highest antimicrobials used for mastitis treatment were ciprofloxacin (83.34%), amoxycillin (80%) and ceftriaxone (76.67%). More than, 70% of S. aureus showed resistance against ampicillin, oxacillin, and tetracycline and more than 60% of E. coli exhibited resistance against oxacillin and sulfamethoxazole-trimethoprim. Selected antimicrobial resistance genes (mecA, tetK, tetL, tetM, tetA, tetB, tetC, sul1, sul2 and sul3) were identified from S. aureus and E. coli. Surprisingly, 7 (7.61%) S. aureus carried the mecA gene and were confirmed as methicillin-resistant S. aureus (MRSA). The most prevalent resistance genes were tetK 18 (19.57%) and tetL 13 (14.13%) for S. aureus, whereas sul1 16 (47.06%), tetA 12 (35.29%), sul2 11 (32.35%) and tetB 7 (20.59%) were the most common resistance genes in E. coli. Indiscriminate use of antimicrobials and the presence of multidrug-resistant bacteria suggest a potential threat to public health.

Development of an advanced flow cytometry based high-resolution immunophenotyping method to benchmark early immune response in dairy cows

The determination of the somatic cell count of a milk sample is one of the most common methods to monitor udder health of a dairy cow. However, this procedure does not take into account the fact that cells in milk present a great variety of different cell types. The objective of our study was to establish a high-resolution differential cell count (HRDCC) by means of flow cytometry in blood and milk. We were able to detect ten subpopulations among the three main populations of immune cells and to determine their viability. Additionally, blood samples were analyzed for common laboratory biomarkers, i.e. differential blood counts, haptoglobin levels and several metabolic parameters. In this first feasibility study, we used three different vaccines to stimulate the immune system of five healthy cows each. Samples were collected shortly before, in between and after the vaccinations. Using multivariate statistical methods we saw a diagnostic benefit when HRDCCs were included compared to only the standard laboratory parameters. The impacts of all three vaccinations on the immune system were visible in blood HRDCCs as well as in milk HRDCCs. Cluster of Differentiation 8⁺ (CD8⁺) T cells, B cells and monocyte/macrophage subpopulations were among the most important and statistically relevant parameters for all treatments in both biofluids. Moreover, in one of the treatment groups intermediate monocytes showed a significant increase after both vaccinations. Although the use of HRDCC in blood or milk was shown to be highly relevant for early systemic diagnostic, to confirm these subpopulations further investigations in cows of different breed, lactation stage or health status are required.

Rapid Detection of Mycoplasma bovis, Staphylococcus aureus and Streptococcus agalactiae in Cattle Bulk Tank Milk in Cyprus and Relations with Somatic Cell Counts

One hundred and seventy-seven (177) bulk tank milk samples were analyzed with a commercially available real-time polymerase chain reaction kit and 11 (6.21%), 41 (23.16%), and 58 (32.77%) tested positive for Mycoplasma bovis, Staphylococcus aureus, and Streptococcus agalactiae, respectively. Statistical analysis revealed a significant relationship between the presence of S. aureus and S. agalactiae. Enumeration of somatic cells was performed in the same samples by flow cytometry. The somatic cell counts were found higher in S. aureus and S. agalactiae positive samples. No association was found between M. bovis presence and somatic cells counts. Low internal assay control Ct values were found to be related with high somatic cell counts. Noticeably, this is the first report for the presence of M. bovis in Cyprus. Therefore, its presence was confirmed by bulk tank milk culture, conventional PCR, and next generation sequencing. Furthermore, M. bovis was typed with multilocus sequencing typing and was allocated to sequence type 29 (ST 29). Real-time PCR in bulk tank milk samples is a useful tool to detect mammary infections, especially for neglected pathogens such as M. bovis.

Rule Discovery in Milk Content towards Mastitis Diagnosis: Dealing with Farm Heterogeneity over Multiple Years through Classification Based on Associations

Simple Summary

Invisible (subclinical) mastitis decreases milk quality and production. Invisible mastitis is linked to an increased use of antimicrobials. The risk of the emergence of antimicrobial-resistant bacteria is a major public health concern worldwide. Therefore, early detection of infected cows is of great importance. Machine learning has opened a new avenue for early mastitis prediction based on simple and accessible milking parameters, such as milk volume, fat, protein, lactose, electrical conductivity (EC), milking time, and milking peak flow. However, farm heterogeneity is a major challenge where multiple patterns can predict mastitis. Here, we employed a classification based on associations and scaling approach for multiple pattern discovery over multiple years. The approach we have developed helps to address farm heterogeneity and generalise machine learning-based diagnosis of mastitis worldwide.

Abstract

Subclinical mastitis, an economically challenging disease of dairy cattle, is associated with an increased use of antimicrobials which reduces milk quantity and quality. It is more common than clinical mastitis and far more difficult to detect. Recently, much attention has been paid to the development of machine-learning expert systems for early detection of subclinical mastitis from milking features. However, differences between animals within a farm as well as between farms, particularly across multiple years, are major obstacles to the generalisation of machine learning models. Here, for the first time, we integrated scaling by quartiling with classification based on associations in a multi-year study to deal with farm heterogeneity by discovery of multiple patterns towards mastitis. The data were obtained from one farm comprising Holstein Friesian cows in Ongaonga, New Zealand, using an electronic automated monitoring system. The data collection was repeated annually over 3 consecutive years. Some discovered rules, such as when the milking peak flow is low, electrical conductivity (EC) of milk is low, milk lactose is low, milk fat is high, and milk volume is low, the cow has subclinical mastitis, reached high confidence (>70%) in multiple years. On averages, over 3 years, low level of milk lactose and high value of milk EC were part of 93% and 83.8% of all subclinical mastitis detecting rules, offering a reproducible pattern of subclinical mastitis detection. The scaled year-independent combinational rules provide an easy-to-apply and cost-effective machine-learning expert system for early detection of hidden mastitis using milking parameters.

Biofilm Research in Bovine Mastitis

Bovine mastitis is one of the most important diseases in the dairy industry and has detrimental impact on the economy and welfare of the animals. Further, treatment failure results in increased antibiotic use in the dairy industry, as some of these mastitis cases for unknown reasons are not resolved despite standard antibiotic treatment. Chronic biofilm infections are notoriously known to be difficult to eradicate with antibiotics and biofilm formation could be a possible explanation for mastitis cases that are not resolved by standard treatment. This paper reviews the current literature on biofilm in bovine mastitis research to evaluate the status and methods used in the literature. Focus of the current research has been on isolates from milk samples and investigation of their biofilm forming properties in vitro. However, in vitro observations of biofilm formation are not easily comparable with the in vivo situation inside the udder. Only two papers investigate the location and distribution of bacterial biofilms inside udders of dairy cows with mastitis. Based on the current knowledge, the role of biofilm in bovine mastitis is still unclear and more in vivo investigations are needed to uncover the actual role of biofilm formation in the pathogenesis of bovine mastitis.

Technical note: Evaluation of a commercial on-farm milk leukocyte differential tester to identify subclinical mastitis cases in dairy cows

The objective of this study was to validate the precision and accuracy of a milk leukocyte differential tester to identify subclinical mastitis cases in dairy cows. Milk samples from individual quarters (n = 320) of 80 Holstein cows were aseptically collected and analyzed in this study. Each sample was divided into 2 replicate samples after mixing. One replicate was analyzed for somatic cell count (SCC) using the current gold standard of flow cytometry immediately after milking. The second sample was evaluated using the on-farm milk leukocyte differential tester directly after milking, where total leukocyte count (TLC; cells/mL) was obtained. The SCC and TLC were used to calculate somatic cell score (SCS) and TLC score [TLS = log₂ (TLC/100,000) + 3]. Two subclinical mastitis thresholds were set: >200,000 (low) and >400,000 (high) cells/mL. First, precision was determined between the 2 methods. Total leukocyte count and calculated TLS from the milk leukocyte differential device were compared with the gold standard using correlation and regression coefficient of determination analyses. Correlation coefficients (r) were 0.97 for TLC and SCC and 0.90 for TLS and SCS. The coefficient of determination for regression (R²) was 0.94 for TLC and SCC and 0.80 for TLS and SCS. Slopes of regression for scores and measures were 0.36 [95% confidence interval (CI): 0.35-0.37] and 0.69 (CI: 0.65-0.73), respectively; both were significantly different from 1. Sensitivity, specificity, and diagnostic accuracy were calculated for correct diagnosis of the 2 SCC thresholds using the gold standard as reference. The sensitivity of the on-farm test was 58% (95% CI: 44 to 71%) and 73% (95% CI: 56 to 86%) for the low and high thresholds, respectively. The specificities for the on-farm test were 100% (95% CI: 99 to 100%) and 100% (95% CI: 98 to 100%) for the low and high thresholds, respectively. Subclinical diagnosis accuracies were 93% (95% CI: 89 to 95%) and 96% (95% CI: 92 to 98%) for the low and high thresholds, respectively. The on-farm milk leukocyte differential tester was precise but not overall accurate for total cell counts; it had high specificity and accuracy for diagnosis compared with a standard diagnostic tool. These results suggest that the tested system is a promising technology to detect subclinical mastitis on-farm.

Genes associated with somatic cell count index in Brown Swiss cattle

Subclinical mastitis (SM) is one of the most common diseases of cows in milk production herds caused by contagious and/or environmental pathogens. Since there are no visible abnormalities in the milk or udder, the detection of SM requires special diagnostic tests. Somatic cell count (SCC) is the most common test used to detect changes in milk due to the inflammatory process. Previously, we developed somatic cell count index (SCCI), a new method for the accurate prediction of milk yield losses caused by elevated SCC. The aim of this study was to identify new candidate genetic markers for SCCI in the Slovenian population of Brown Swiss (BS) cattle. For that purpose, we analyzed samples of BS cows, which were genotyped using single-nucleotide polymorphism (SNP) microarray ICBF International Dairy and Beef v3 (ICBF, Ireland) for a total of 53,262 SNP markers. After quality control, the set of 18,136 SNPs was used in association analysis. Our association analysis revealed that 130 SNPs were associated with SCCI, which were used for haplotype and overlap analysis. Haplotypes generated from the genotyped data for those 130 SNPs revealed 10 haplotype blocks among 22 SNPs. Additionally, all 130 SNPs, mastitis-related quantitative trait loci, and protein-coding genes are shown on the bovine genome. Overlap analysis shows that the majority of significantly associated SNPs (70) are intergenic, while 60 SNPs are mapped within, upstream, or downstream of the protein-coding genes. However, those genes can serve as strong candidate genes for the marker-assisted selection programs in our and possibly other populations of cattle.

Molecular characterization of KPC-2-producing Klebsiella pneumoniae ST258 isolated from bovine mastitis

Bovine mastitis, an inflammation of the mammary gland of dairy cattle, is the most prevalent disease causing economically important losses, reduced milk production, early culling, veterinary expenses, and higher death rates. Bovine mastitis infections are the main cause for the use of antibiotics; however, the emergence of multidrug-resistant bacteria and the poor or nil response to antibiotics has become a critical global health problem. The goal of this study was the characterization of bacterial infections associated with clinical bovine mastitis. All the isolates were multidrug-resistant and were negative for the production of extended spectrum β-lactamases. However, all isolates were identified as carbapenemase-producing organisms by the Carba NP test. The carbapenemase identified was the product of the KPC-2 gene. The isolates were identified as Klebsiella pneumoniae and contained virulence genes for fimbriae, lipopolysaccharides, nitrogen starvation genes, and siderophores. Sixty-nine percent of the KPC-2-producing isolates had the same plasmid profile, although the genetic mobilization of resistance by bacterial conjugation was unsuccessful. The carbapenemase corresponded to the plasmid-borne KPC-2 gene identified by Southern blot hybridization. The assay showed a positive signal in the 90 kb (69% of the isolates), 165 kb (31% of the isolates), and 130 kb (6% of the isolates) plasmids. The IncFII_y and IncFII_k replicons were detected among these K. pneumoniae isolates. The PFGE and MLST analysis showed that all of the isolates are comprised by two clones (A and B) belonging to Sequence Type 258. This is the first report of K. pneumoniae producing carbapenemase KPC-2 isolated from bovine mastitis.

Effect of subclinical mastitis detected in the first month of lactation on somatic cell count linear scores, milk yield, fertility, and culling of dairy cows in certified organic herds

It is well established that subclinical mastitis (SCM), characterized by somatic cell count (SCC) >200,000 cells/mL, has a negative effect on the productivity, reproductive performance, and survivability of cows from conventional dairy herds. However, in organic herds, where the use of antimicrobial drugs is restricted for the treatment and control of intramammary infections (IMI) in dairy cows, little is known about the effect of SCM on performance and survivability. The objective of this study was to evaluate whether SCM diagnosed during the first month of lactation was associated with SCC linear score dynamics, milk production, fertility, and culling of dairy cows in USDA-certified organic herds. We collected data from 2 organic herds in New Mexico and Texas. A total of 1,511 cows that calved between June 2018 and May 2019 were included in the study and were followed until month 10 of the current lactation. Cows with SCC >200,000 cells/mL in the first month of lactation were considered to have SCM. We used mixed linear regression models accounting for repeated measures to assess the effect of SCM on monthly milk production and SCC linear scores. We used Cox proportional hazards models to evaluate the effect of SCM on the risk of pregnancy and culling. We considered parity, farm, previous gestation length, stillbirth, twinning, dystocia, and 2- and 3-way interactions as potential confounders. Cows diagnosed with SCM during the first month of lactation produced less milk than cows without SCM. Cows with SCM had elevated SCC linear scores during their previous lactation and throughout the subsequent months of lactation compared to cows without SCM. The effect of SCM on SCC linear scores was more pronounced in multiparous than primiparous cows. Subclinical mastitis during the first month of lactation did not affect the likelihood of pregnancy during the first 300 d in milk. Cows with SCM in the first month were more likely to die or be culled during the 300 d of lactation than cows without SCM. We observed that elevated SCC in the first month of lactation had detrimental effects on the milk yield and survivability of dairy cows in USDA organic herds, but it did not affect reproductive performance. We demonstrated that cows with SCM diagnosed in the first month of lactation continued to have elevated SCC linear scores throughout their entire lactation, and that elevated SCC was carried over from the previous lactation.