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.

A randomized, controlled trial examining quarter-level somatic cell count and culture-based selective dry cow therapy against blanket dry cow therapy on early-lactation production outcomes

The objective of this study was to determine quarters requiring antimicrobial treatment using either a benchtop somatic cell counter (S-SDCT) or culture with gram-positive selective media (C-SDCT) and compare outcomes in these cows to those receiving blanket dry cow therapy (BDCT) in a randomized, controlled trial. Two novel methods of identifying cows with intramammary infections followed by selective antimicrobial treatment were evaluated at a commercial dairy farm to determine their usefulness in decreasing antibiotic usage during the dry period without significant detrimental effects on milk quality and production. Cows (n = 840) were randomly allocated to one of 3 groups (BDCT, C-SDCT, S-SDCT) the day before dry-off and quarter-level milk samples (QLMS) were collected. The QLMS from cows in the S-SDCT group were evaluated using the cell counter and quarters were treated if somatic cell count (SCC) was ≥200,000 cells/mL, while QLMS from cows in the C-SDCT group were cultured and quarters were treated if the culture showed growth. All cows in the BDCT received antimicrobial therapy and all cows received an internal teat sealant regardless of treatment group. Outcomes measured were first and second DHIA test somatic cell count, milk production through 60 d in milk, cows leaving the farm, clinical mastitis, and bacteriologic new infections in a subset of quarters. Cows in both SDCT groups had fewer antimicrobial treatments than cows in the BDCT group as was expected, and cows in the C-SDCT group had fewer treatments than those in the S-SDCT group. Cows in both SDCT groups had higher linear score at the first DHIA test (BDCT: 1.8, S-SDCT: 2.2, C-SDCT: 2.2), however there were no other differences between groups regarding any other outcomes measured. While antimicrobial use was significantly reduced, farms should use caution in adopting the benchtop analyzer and the selective media described in this study as ways to identify infected cows for dry cow therapy as they may result in increased linear score early in lactation.

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.

Novel insights into the associations between immune cell population distribution in mammary glands and milk minerals in Holstein cows

Udder health has a crucial role in sustainable milk production, and various reports have pointed out that changes in udder condition seem to affect milk mineral content. The somatic cell count (SCC) is the most recognized indicator for the determination of udder health status. Recently, a new parameter, the differential somatic cell count (DSCC), has been proposed for a more detailed evaluation of intramammary infection patterns. Specifically, the DSCC is the combined proportions of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) on the total SCC, with macrophages (MAC) representing the remainder proportion. In this study, we evaluated the association between DSCC in combination with SCC on a detailed milk mineral profile in 1,013 Holstein-Friesian cows reared in 5 herds. An inductively coupled plasma-optical emission spectrometry was used to quantify 32 milk mineral elements. Two different linear mixed models were fitted to explore the associations between the milk mineral elements and first, the DSCC combined with SCC, and second, DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the proportion of PMN-LYM and MAC by SCC. We observed a significant positive association between SCC and milk Na, S, and Fe levels. Differential somatic cell count showed an opposite behavior to the one displayed by SCC, with a negative association with Na and positive association with K milk concentrations. When considering DSCC as count, Na and K showed contrasting behavior when associated with PMN-LYM or MAC counts, with decreasing of Na content and increasing K when associated with increasing PMN-LYM counts, and increasing Na and decreasing K when associated with increasing MAC count. These findings confirmed that an increase in SCC is associated with altered milk Na and K amounts. Moreover, MAC count seemed to mirror SCC patterns, with the worsening of inflammation. Differently, PMN-LYM count exhibited patterns of associations with milk Na and K contents attributable more to LYM than PMN, given the nonpathological condition of the majority of the investigated population. An interesting association was observed for milk S content, which increased with increasing of inflammatory conditions (i.e., increased SCC and MAC count) probably attributable to its relationship with milk proteins, especially whey proteins. Moreover, milk Fe content showed positive associations with the PMN-LYM population, highlighting its role in immune regulation during inflammation. Further studies including individuals with clinical condition are needed to achieve a comprehensive view of milk mineral behavior during udder health impairment.

A First Investigation into the Use of Differential Somatic Cell Count as a Predictor of Udder Health in Sheep

Differential somatic cell count (DSCC), the percentage of somatic cell count (SCC) due to polymorphonuclear leukocytes (PMNs) and lymphocytes (LYMs), is a promising effective diagnostic marker for dairy animals with infected mammary glands. Well-explored in dairy cows, DSCC is also potentially valid in sheep, where clinical and subclinical mastitis outbreaks are among the principal causes of culling. We pioneered the application of DSCC in dairy ewes by applying receiver-operating characteristic (ROC) curve analysis to define the most accurate thresholds to facilitate early discrimination of sheep with potential intramammary infection (IMI) from healthy animals. We tested four predefined SCC cut-offs established in previous research. Specifically, we applied SCC cut-offs of 265 × 103 cells/mL, 500 × 103 cells/mL, 645 × 103 cells/mL, and 1000 × 103 cells/mL. The performance of DSCC as a diagnostic test was assessed by examining sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), and area under curve (AUC) analyses. The designated threshold value for DSCC in the detection of subclinical mastitis is established at 79.8%. This threshold exhibits Se and Sp of 0.84 and 0.81, accompanied by an AUC of 0.88. This study represents the inaugural exploration of the potential use of DSCC in sheep's milk as an early indicator of udder inflammation.

Comparison of an image cytometry somatic cell count analyzer to a flow cytometry analyzer

The objective of this study was to evaluate the performance of a small footprint benchtop somatic cell counter based on image cytometry (LactiCyte HD; Page and Pedersen International Ltd., Hopkinton, MA) against a flow cytometer employed at a regional dairy herd improvement (DHI) laboratory. Milk samples collected during monthly DHI testing were split into 2 samples. One sample was evaluated using flow cytometry (Bentley SomaCount FCM; Bentley Instruments, Chaska, MN) at the regional DHI laboratory, whereas the other was evaluated using image cytometry at 2 different image levels (full number of images, 16 pictures per slide; half number of images, 8 pictures per slide). Mean bias of the image cytometer at 16 images was -15,500 cells/mL, whereas at 8 images the bias was 21,800 cells/mL. When considering only cell counts ≤400,000 cells per mL, the bias for both imaging resolutions was positive, meaning the image cytometer read higher than the flow cytometer. Both imaging resolutions (16 and 8) had a concordance correlation coefficient greater than 0.95. Considering ≥200,000 cells/mL to be indicative of subclinical mammary gland infection, the sensitivity and specificity of the image cytometer at 16 images were 92.0% and 91.7%, whereas the sensitivity and specificity of the analyzer at 8 images were 92.0% and 85.7%, respectively. Method precision (repeatability; coefficients of variation) were calculated at 3 different somatic cell counts (100,000, 200,000, and 400,000 cells/mL) where each sample was run repeatedly 12 times. When analyzed at the full number of images the coefficients of variation were 16.9%, 11.7%, and 10.9% for 100,000, 200,000, and 400,000 cells/mL, respectively. Analysis at half the number of images resulted in coefficients of variation of 18.9%, 24.8%, and 8.7% for 100,000, 200,000, and 400,000 cells/mL. We conclude that the image cytometer is an acceptable somatic cell count analyzer for on-farm use for applications such as screening cows for microbiological testing, and that precision is superior when the analysis is performed at the full number of images allowed by the instrument.

Multinomial logistic regression based on neural networks reveals inherent differences among dairy farms depending on the differential exposure to Fasciola hepatica and Ostertagia ostertagi

Fasciola hepatica and Ostertagia ostertagi are cattle parasites with worldwide relevance for economic outcome as well as animal health and welfare. The on-farm exposure of cattle to both parasites is a function of host-associated, intrinsic, as well as environmental and farm-specific, extrinsic, factors. Even though knowledge on the biology of both parasites exists, sophisticated and innovative modelling approaches can help to deepen our understanding of key aspects fostering the exposure of dairy cows to these pathogens. In the present study, multiple multinomial logistic regression models were fitted via neural networks to describe the differences among farms where cattle were not exposed to either F. hepatica or O. ostertagi, to one parasite, or to both, respectively. Farm-specific production and management characteristics were used as covariates to portray these differences. This elucidated inherent farm characteristics associated with parasite exposure. In both studied regions, pasture access for cows, farm-level milk yield, and lameness prevalence were identified as relevant factors. In region 'South', adherence to organic farming principles was a further covariate of importance. In region 'North', the prevalence of cows with a low body condition score, herd size, hock lesion prevalence, farm-level somatic cell count, and study year appeared to be of relevance. The present study broadens our understanding of the complex epidemiological scenarios that could predict differential farm-level parasite status. The analyses have revealed the importance of awareness of dissimilarities between farms in regard to the differential exposure to F. hepatica and O. ostertagi. This provides solid evidence that dynamics and relevant factors differ depending on whether or not cows are exposed to F. hepatica, O. ostertagi, or to both.

Udder health-related traits in cow milk: phenotypic variability and effect on milk yield and composition

The milk differential somatic cell count (DSCC) has been proposed in recent years as a mean by which to better monitor the udder health status (UHS) in dairy cows. Milk DSCC is the amount of polymorphonuclear neutrophils and lymphocytes contributing to the total somatic cell count (SCC) and can be determined on a routine basis in individual milk samples subjected to official analysis. In the present study, 522 865 milk test-day records of 77 143 cows were scrutinised to identify factors affecting the variability of both DSCC and SCC in Holstein Friesian, Jersey, Simmental and Rendena cows through linear mixed models. The fixed effects were breed, parity, lactation stage, sampling season, and all the first-order interactions of breed. Cow and herd-test-date were considered as random. Subsequently, four UHS groups were created (1: SCC ≤ 200 000 cells/mL and DSCC ≤ 65%; 2: SCC ≤ 200 000 cells/mL and DSCC > 65%; 3: SCC > 200 000 cells/mL and DSCC > 65%; 4: SCC > 200 000 cells/mL and DSCC ≤ 65%) to compare milk yield and quality. Milk SCS and DSCC differed across lactation, parity, sampling season and breed. In particular, Simmental cows had the lowest SCC and Jersey the lowest DSCC. Depending on the breed, UHS affected daily milk yield and composition to a different extent. The UHS group 4, i.e. the one grouping test-day records with high SCC and low DSCC, presented the lowest estimate of milk yield and lactose content no matter the breeds. Our findings support that udder health-related traits (SCS and DSCC) are useful information to improve udder health at individual cow and herd levels. Moreover, the combination of SCS and DSCC is useful to monitor milk yield and composition.

Neutrophils expressing major histocompatibility complex class II molecules circulate in blood and milk during mastitis and show high microbicidal activity

Bovine mastitis is mainly caused by bacterial infection and is responsible for important economic losses as well as alterations of the health and welfare of animals. The increase in somatic cell count (SCC) in milk during mastitis is mainly due to the influx of neutrophils, which have a crucial role in the elimination of pathogens. For a long time, these first-line defenders have been viewed as microbe killers, with a limited role in the orchestration of the immune response. However, their role is more complex: we recently characterized a bovine neutrophil subset expressing major histocompatibility complex class II (MHC-II) molecules (MHC-II^pos), usually distributed on antigen-presenting cells, as having regulatory capacities in cattle. In this study, our objective was to evaluate the implication of different neutrophils subsets in the mammary gland immunity during clinical and subclinical mastitis. Using flow cytometry, we analyzed the presence of MHC-II^pos neutrophils in blood and in milk during clinical mastitis at different time points of inflammation (n = 10 infected quarters) and during subclinical mastitis, defined as the presence of bacteria and an SCC >150,000 cells/mL (n = 27 infected quarters). Our results show, for the first time, that in blood and milk, neutrophils are a heterogeneous population and encompass at least 2 subsets distinguishable by their expression of MHC-II. In milk without mastitis, we observed higher production of reactive oxygen species and higher phagocytosis capacity of MHC-II^pos neutrophils compared with their MHC-II^neg counterparts, indicating the high bactericidal capacities of MHC-II^pos neutrophils. MHC-II^pos neutrophils are enriched in milk compared with blood during subclinical mastitis but not during clinical mastitis. Moreover, we observed a positive and highly significant correlation between MHC-II^pos neutrophils and T lymphocytes present in milk during subclinical mastitis. Our experiments involved a total of 47 cows (40 Holstein and 7 Normande cows). To conclude, our study opens the way to the discovery of new biomarkers of mastitis inflammation.

Sodium and Potassium Concentrations and Somatic Cell Count of Human Milk Produced in the First Six Weeks Postpartum and Their Suitability as Biomarkers of Clinical and Subclinical Mastitis

The sodium (Na) concentration and the ratio of Na to potassium (K; Na/K) in human milk are used commonly as biomarkers of subclinical mastitis, but limited data exist on their relationship to and ability to predict clinical mastitis. Here, we assessed concentrations of Na, K, Na/K, and somatic cell count (SCC), a mammary health biomarker used in the dairy industry, in milk prospectively collected from both breasts of 41 women over the first 6 weeks postpartum. Although values differed over time postpartum, there were no differences in mean values between breasts. Nearly one-quarter (24%) of participants experienced clinical mastitis. Somatic cell counts >4.76 × 105 cells/mL were most strongly related to development of clinical mastitis in the following week (odds ratio, 7.81; 95% CI, 2.15−28.30; p = 0.002), although relationships were also observed for SCC > 4.00 × 105 cells/mL and Na concentration >12 mmol/L. Estimates of the prevalence of subclinical mastitis in women who never progressed to clinical mastitis differed by biomarker but ranged from 20 to 75%. Despite these findings, positive predictive values (PPV) of the biomarkers for identifying clinical mastitis were low (≤0.34), indicating additional research is needed to identify single biomarkers or composite measures that are highly specific, sensitive, and predictive of clinical mastitis in women.

Relationship between total and differential quarter somatic cell counts at dry-off and early lactation

Mastitis is a most common disease of dairy cows and causes tremendous economic loss to the dairy industry worldwide. Somatic cell counts (SCC) reflect the inflammatory response to infections and is a metric used as key indicator in mastitis screening programs, typically within the framework of national milk recording schemes. Besides the determination of total SCC, the differentiation of cell types has been described to be beneficial for a more definite description of the actual udder health status of dairy cows. Differential somatic cell count (DSCC) represents the combined proportion of polymorphonuclear leukocytes (PMN) and lymphocytes expressed as a percentage of the total. The aim of this study was to investigate the relationship between SCC and differential somatic cell count (DSCC) in individual quarter milk samples collected at different time points: at dry-off, after calving and at the lactation peak. We used individual quarter data from farms representing the specialized production system of Parmigiano Reggiano cheese in Northern Italy. Average DSCC values ranged between 44.9% and 56.3%, with higher values (60.4%-72.1%) in milk samples with ≥ 1 million SCC/ml (where the proportion of samples with DSCC > 70% can be as high as 0.73). Moderate overall correlations between DSCC and log(SCC) were estimated (Pearson = 0.42, Spearman = 0.38), with a clear increasing trend with parity and around the lactation peak (e.g. Pearson = 0.59 at 60 DIM in parity 4). Taking SCC values as indicators of subclinical mastitis, DSCC would diagnose mastitis with 0.75 accuracy. Data editing criteria do have an impact on results, with stricter filtering leading to lower correlations between log(SCC) and DSCC. In conclusion DSCC and SCC provide different descriptions of the udder health status of dairy cows which, at least to some extent, are independent. DSCC alone doesn't provide more accurate information than SCC at quarter level but, used in combination with SCC, can be of potential interest within the framework of milk recording programs, especially in the context of selective dry-cow therapy (SDCT). However, this needs further investigation and updated threshold values need to be selected and validated.

Prediction of fresh and ripened cheese yield using detailed milk composition and udder health indicators from individual Brown Swiss cows

The composition of raw milk is of major importance for dairy products, especially fat, protein, and casein (CN) contents, which are used worldwide in breeding programs for dairy species because of their role in human nutrition and in determining cheese yield (%CY). The aim of the study was to develop formulas based on detailed milk composition to disentangle the role of each milk component on %CY traits. To this end, 1,271 individual milk samples (1.5 L/cow) from Brown Swiss cows were processed according to a laboratory model cheese-making procedure. Fresh %CY (%CY_CURD), total solids and water retained in the fresh cheese (%CY_SOLIDS and %CY_WATER), and 60-days ripened cheese (%CY_RIPENED) were the reference traits and were used as response variables. Training-testing linear regression modeling was performed: 80% of observations were randomly assigned to the training set, 20% to the validation set, and the procedure was repeated 10 times. Four groups of predictive equations were identified, in which different combinations of predictors were tested separately to predict %CY traits: (i) basic composition, i.e., fat, protein, and CN, tested individually and in combination; (ii) udder health indicators (UHI), i.e., fat + protein or CN + lactose and/or somatic cell score (SCS); (iii) detailed protein profile, i.e., fat + protein fractions [CN fractions, whey proteins, and nonprotein nitrogen (NPN) compounds]; (iv) detailed protein profile + UHI, i.e., fat + protein fractions + NPN compounds and/or UHI. Aside from the positive effect of fat, protein, and total casein on %CY, our results allowed us to disentangle the role of each casein fraction and whey protein, confirming the central role of β-CN and κ-CN, but also showing α-lactalbumin (α-LA) to have a favorable effect, and β-lactoglobulin (β-LG) a negative effect. Replacing protein or casein with individual milk protein and NPN fractions in the statistical models appreciably increased the validation accuracy of the equations. The cheese industry would benefit from an improvement, through genetic selection, of traits related to cheese yield and this study offers new insights into the quantification of the influence of milk components in composite selection indices with the aim of directly enhancing cheese production.

Direct labeling of milk cells without centrifugation for counting total and differential somatic cells using flow cytometry

Somatic cell count (SCC) in milk is an essential indicator for defining and managing udder health. However, analyzing differential SCC (dSCC) can be helpful in determining the type or evolution stage of mastitis. A high abundance of polymorphonuclear cells (PMN) is associated with acute mastitis; however, the status of a chronic disease is less well characterized. A method capable of analyzing SCC and dSCC can prove to be a helpful tool for monitoring the status of evolution of mastitis disease in a better way. Therefore, a new direct-flow cytometry method was developed to count and differentiate somatic cells in milk without the steps of centrifugation or washing, avoiding variabilities that occur due to enrichment or loss of specific cell types. In this new method, SCC is analyzed using the method of DNA staining with Hoechst stain, whereas dSCC are analyzed using specific antibodies targeting 2 main cell types associated with mastitis: PMN cells and antigen-presenting cells, which are associated with innate and adaptive immunity. Equivalent SCC values were obtained between the new method and the routine ISO 13366-2 method in a comparison of 240 raw milk samples. Furthermore, dSCC results were confirmed by microscopy after May-Gründwald-Giemsa staining in 165 quarter milk samples from healthy and diseased cows. The method was verified with fluorescence microscopy on the 2 targeted cell types and in raw milk samples. The newly developed method is independent of any instrument and can be further designed to differentiate other cell types and animal species by selecting appropriate antibodies.

Impact of somatic cell count combined with differential somatic cell count on milk protein fractions in Holstein cattle

Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely α_S1-CN, α_S2-CN, κ-CN, and β-CN, and 3 whey protein fractions, namely β-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with α_S1-CN, β-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both β-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.

Streptococcus agalactiae and Prototheca spp. induce different mammary gland leukocyte responses in Holstein cows

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Streptococcus agalactiae increased polymorphonuclear neutrophils in milk samples.

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Prototheca infection greatly increased total T lymphocytes and T-helper lymphocytes in milk samples.

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Prototheca spp. trigger an adaptive immune response and chronic inflammation.

In this study, we investigated the association between natural subclinical intramammary infection (IMI) caused by Streptococcus agalactiae and Prototheca spp. and milk differential cell counts assessed by cytofluorimetric analysis in Holstein cows. After an initial bacteriological screening on 188 animals and a second assessment carried out 2 wk later aimed at confirming the bacteriological status, we collected milk samples from 47 animals and performed (1) milk composition analyses; (2) somatic cell counts and differential somatic cell counts (DSCC); and (3) cytofluorimetric analyses. Before statistical analyses, animals with co-infections were filtered out. Bacteriological status (negative, positive for Strep. agalactiae, or positive for Prototheca spp.) significantly affected the investigated traits. Compared with culture-negative samples, those that were positive for Strep. agalactiae and Prototheca spp. had higher SCS (+61% and +49%, respectively), DSCC (+4% and +19%, respectively), log polymorphonuclear neutrophil (PMN)-lymphocyte (LYM) counts (+59% and +71%, respectively), and log macrophage (MAC) counts (+63% and +72%, respectively). The individual leukocyte populations determined by cytofluorimetric analysis confirmed that mastitis infection increased the proportion of PMN in the milk samples compared with culture-negative samples, particularly when caused by Strep. agalactiae (+51%). In the case of MAC, the 2 pathogens behaved in opposite ways: Strep. agalactiae increased MAC by 41%, whereas Prototheca decreased MAC by 25%. Prototheca infection strongly increased the proportion of total T lymphocytes (TL; +87%) and T-helper lymphocytes (+83%). Accordingly, the (PMN+MAC):TL ratio increased with Strep. agalactiae infection (+95%) and decreased with Prototheca infection (−43%) compared with culture-negative samples. These results suggest the prevalence of an adaptive immune response and chronic inflammation in Prototheca infection, and an innate immune response to Strep. agalactiae. This knowledge might provide an important contribution to the development of novel and effective diagnostics and therapeutics.

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.

Identification of Inflammatory and Regulatory Cytokines IL-1α-, IL-4-, IL-6-, IL-12-, IL-13-, IL-17A-, TNF-α-, and IFN-γ-Producing Cells in the Milk of Dairy Cows with Subclinical and Clinical Mastitis

In naturally occurring bovine mastitis, effects of infection depend on the host inflammatory response, including the effects of secreted cytokines. Knowledge about the inflammatory and regulatory cytokines in milk cells of free-stall barn dairy cows and in naturally occurring mastitis is lacking as most studies focus on induced mastitis. Hereby, the aim of the study was to determine inflammatory and regulatory cytokines in the milk of dairy cows with subclinical and clinical mastitis. The following examinations of milk samples were performed: differential counting of somatic cells (SCC), bacteriological examination, and immunocytochemical analysis. Mean SCC increased in subclinical and clinical mastitis cases. The number of pathogenic mastitis-causing bacteria on plates increased in subclinical mastitis cases but decreased in clinical mastitis. The inflammatory and regulatory markers in the milk cells of healthy cows showed the highest mean cell numbers (%). In mastitis cases, immunoreactivity was more pronounced for IL-4, IL-6, IL-12, IL-13, IL-17A, TNF-α, and IFN-γ. Data about subclinical and clinical mastitis demonstrate inflammatory responses to intramammary infection driven by IL-1α, IL-4, and IL-17A. Moreover, the host defense response in mastitis is characterized by continuation or resolution of initial inflammation. IL-12 and INF-γ immunoreactivity was recognized to differ mastitis cases from the relative health status.

Quarter-level analyses of the associations among subclinical intramammary infection and milk quality, udder health, and cheesemaking traits in Holstein cows

In this study, we investigated associations among subclinical intra-mammary infection (IMI) and quarter-level milk composition, udder health indicators, and cheesemaking traits. The dataset included records from 450 Holstein cows belonging to three dairy herds. After an initial screening (T0) to identify animals infected by Streptococcus agalactiae, Streptococcus uberis, Staphylococcus aureus, and Prototheca spp., 613 quarter milk samples for 2 different sampling times (T1 and T2, 1 mo after T1) were used for analysis. Milk traits were analyzed using a hierarchical linear mixed model including the effects of days in milk, parity and herd, and bacteriological and inflammatory category [culture negative with somatic cell count (SCC) <200,000 cells/mL; culture negative with SCC ≥200,000 cells/mL; or culture positive]. All udder health indicators were associated with increased SCC and IMI at both sampling times. The largest effects were detected at T2 for milk lactose (-7% and -5%) and milk conductivity (+9% and +8%). In contrast, the increase in differential SCC (DSCC) in samples with elevated SCC was larger at T1 (+17%). Culture-negative samples with SCC ≥200,000 cells/mL had the highest SCC and greatest numbers of polymorphonuclear-neutrophils-lymphocytes and macrophages at both T1 and T2. Regarding milk cheesemaking ability, samples with elevated SCC showed the worst pattern of curd firmness at T1 and T2. At T2, increased SCC and IMI induced large decreases in recoveries of nutrients into the curd, in particular recovered protein (-14% and -16%) and recovered fat (-12% and -14%). Different behaviors were observed between Strep. agalactiae and Prototheca spp., especially at T2. In particular, samples that were positive for Strep. agalactiae had higher proportions of DSCC (+19%) compared with negative samples with low SCC, whereas samples that were positive for Prototheca spp. had lower DSCC (-11%). Intramammary infection with Prototheca spp. increased milk pH compared with culture-negative samples (+3%) and negative samples that had increased SCC (+2%). The greatest impairment in curd firmness at 30 min from rennet addition was observed for samples that were positive for Prototheca spp. (-99% compared with negative samples, and -98% compared with negative samples with high SCC). These results suggest that IMI caused by Prototheca spp. have detrimental effects on milk technological traits that deserve further investigation of the mechanisms underlying animals' responses to infection.

Rapid determination of pathogens in mastitic milk of dairy cows using Gram staining

This study aimed to determine whether causative pathogens in mastitic milk can be determined by Gram staining after the centrifugation of milk. Gram staining was performed using unconcentrated and concentrated milk cells. Using this method, we found that the background of microscopic image of unconcentrated milk cells was complex and bacteria were difficult to detect. In contrast, the background of the smears in the concentrated milk cells was translucent, and bacterial and somatic cells were clearly visible. The sensitivity and specificity of the Gram staining of concentrated milk cells were 84.4% and 86.0% and 50.0% and 94.5% for the detection of gram-positive and gram-negative bacteria, respectively. The presented method provides a simple and inexpensive means of determining mastitis-causing pathogens.

Validation of somatic cell score-associated SNPs from Holstein cattle in Sudanese Butana and Butana × Holstein crossbred cattle

The Bos indicus zebu cattle Butana is the most commonly used indigenous dairy cattle breed in Sudan. In the last years, high-yielding Holstein dairy cattle were introgressed into Butana cattle to improve their milk yield and simultaneously keep their good adaption to extreme environmental conditions. With the focus on the improvement of milk production, other problems arose such as an increased susceptibility to mastitis. Thus, genetic selection for mastitis resistance should be considered to maintain healthy and productive cows. In this study, we tested 10 single nucleotide polymorphisms (SNPs) which had been associated with somatic cell score (SCS) in Holstein cattle for association with SCS in 37 purebred Butana and 203 Butana × Holstein crossbred cattle from Sudan. Animals were genotyped by competitive allele-specific PCR assays and association analysis was performed using a linear mixed model. All 10 SNPs were segregating in the crossbred Butana × Holstein populations, but only 8 SNPs in Sudanese purebred Butana cattle. The SNP on chromosome 13 was suggestively associated with SCS in the Butana × Holstein crossbred population (rs109441194, 13:79,365,467, P_BF = 0.054) and the SNP on chromosome 19 was significantly associated with SCS in both populations (rs41257403, 19:50,027,458, Butana: P_BF = 0.003, Butana × Holstein: P_BF = 6.2 × 10⁻¹⁶). The minor allele of both SNPs showed an increase in SCS. Therefore, selection against the disadvantageous minor allele could be used for genetic improvement of mastitis resistance in the studied populations. However, investigations in a bigger population and across the whole genome are needed to identify additional genomic loci.

Graduate Student Literature Review: Systemic mediators of inflammation during mastitis and the search for mechanisms underlying impaired lactation

The negative effect of mastitis on lactation is well established, yet the mechanisms causing reduced milk production in the afflicted dairy cow are not. As one of the major inflammatory diseases in the dairy industry, mastitis has rightly received considerable research interest for decades. However, the focus on distinct, pathologic effects in mastitic glands has largely overlooked systemic effects on noninflamed mammary glands. This is particularly evident in the severe, acute response to the potent inflammatory mediator, lipopolysaccharide (LPS). Whereas secretory cell death, impaired tight junctions, and migration of leukocytes are locally restricted to an inflamed, LPS-challenged gland, changes in milk yield and milk components may be detectable in all mammary glands. Further, these differences extend to the mammary transcriptome. Notably, few transcriptomic studies have been designed to test for effects of systemic mediators of inflammation on gene expression. Relevant changes in the noninflamed mammary gland, identified through biochemical analyses and transcriptional studies, warrant further research. Current evidence suggests proinflammatory cytokines play a role in regulating lactose synthesis, but additional candidates and mechanisms continue to be identified. Ultimately, understanding how systemic mediators of inflammation affect mammary function may lead to the development of interventions that enable more efficient milk production without sacrificing the benefits of inflammation.

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.

Dynamics of Macrophages and Polymorphonuclear Leukocytes Milk-Secreted by Buffaloes with Udders Characterized by Different Clinical Status

The study evaluated the dynamics of macrophages and polymorphonuclear leukocytes milk-secreted by Mediterranean Buffaloes (MBs). Sixty quarter-milk-samples were collected and divided into three groups (n = 20 units each one): clinical mastitis (CM), subclinical mastitis (SCM), and intramammary infection (IMI). The control group consisted of an additional 20 healthy quarters. Their health status was assessed by clinical examination, quantitative somatic cell count (QSCC) and bacteriological milk culture. Finally, a differential somatic cell count (DSCC) was performed on all the milk samples. The mean percentage of macrophages, both in CM- and SCM-quarters, showed a significant difference as compared with the healthy-ones. Significant differences were also detected comparing the mean percentages of polymorphonuclear leukocytes between CM- and healthy-quarters, SCM and healthy, IMI and healthy. The QSCC revealed a weak-significant-negative-correlation with the quantitation of macrophages (r = −0.388), and a moderate-significant-positive-correlation with the polymorphonuclear leukocytes (r = 0.477). Macrophages and polymorphonuclear leukocytes showed a weak-significant-negative-correlation between them (r = −0.247). The interpretation of macrophages and polymorphonuclear leukocytes dynamics in milk provided beneficial information regarding the clinical status of the quarters enrolled. Future studies exploring the potential use of DSCC to improve udder health represent an interesting perspective in these ruminants.

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k₂₀), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCT_eq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CF_max), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CF_max (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCT_eq (0.53 and 0.41), t_max (0.38 and 0.48). Log MAC count was correlated with k₂₀ (+0.34), and log PMN-LYM count was correlated with CF_max (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

The relationship of bovine milk somatic cell count to neutrophil level in samples of cow's milk assessed by an automatic cell counter

This research communication describes the application of a fluorescent automatic cell counter Lactoscan SCC for simultaneous determination of somatic cell count and neutrophils in bovine milk. The obtained results were compared with results obtained by a flow cytometer and a light microscope. The Pearson correlations between the methods were calculated. A comparison between the main characteristics of the three kinds of analysis was made - the assay duration and the intra-assay precision. A relation between the SCC and neutrophil cells was observed in 55 milk samples. The obtained results confirm that the simultaneous determination of SCC and neutrophil analysis are necessary and support the early diagnosis of mastitis, the timely treatment of the animal and the avoidance of major economic losses.

Associations between different udder health groups defined based on a combination of total and differential somatic cell count and the future udder health status of dairy cows

Mastitis, in particular in its subclinical form, which may spread unnoticeable within a herd, continues to be a major challenge in the dairy industry. Somatic cell count (SCC) is a broadly used proxy for subclinical mastitis. The recently introduced Differential SCC (DSCC) representing the combined proportion of polymorphonuclear neutrophils and lymphocytes as a percentage of total SCC, can be used in combination with SCC to categorise cows into four different udder health groups (UHG) depending on actual test day results: 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 objective of our study was to investigate to what extent the UHG aid in determining different statuses of cows: I) leaving herd before next test day, II) having >200,000 cells/mL at the next test day, and III) having ≤200,000 cells/mL at the next 3 test days. Multivariable logistic regression analysis was used to evaluate these statuses based on routinely generated dairy herd improvement (DHI) data from Austria, China, Estonia, Germany, and Spain. Cows in groups C (odds ratio (OR): 2.13, 95 % confidence interval (CI): 1.95-2.34) and, particularly, D (OR: 3.91, 95 % CI: 3.31-4.62) were significantly more likely to leave herds compared to cows in group A. Late-lactating cows indicated the highest likelihood (OR: 16.03, 95 % CI: 14.44-17.81) to leave herds in our analysis. Interestingly, we found that cows in UHG B had significantly higher odds (OR: 2.77, 95 % CI: 2.58-2.98) to have >200,000 cells/mL at the next test day compared to cows in group A. As anticipated, cows in UHG B (OR: 0.40, 95 % CI: 0.38-0.42), C (OR: 0.08, 95 % CI: 0.07-0.09), and D (OR: 0.16, 95 % CI: 0.14-0.19) each were significantly less likely to have ≤200,000 cells/mL at the next 3 test days compared to cows in group A. Above described results are an example from Germany, but the same trends could be seen across all countries considered in our study. In conclusion, our findings illustrate that the UHG concept reveals additional valuable information about udder health and culling based a single test day over working with SCC only. Actual decisions in day-to-day farm management that could be taken were not investigated here and need to be further explored.

New Insights into the Significance of PARP-1 Activation: Flow Cytometric Detection of Poly(ADP-Ribose) as a Marker of Bovine Intramammary Infection

Bovine intramammary infections are common diseases affecting dairy cattle worldwide and represent a major focus of veterinary research due to financial losses and food safety concerns. The identification of new biomarkers of intramammary infection, useful for monitoring the health of dairy cows and wellness verification, represents a key advancement having potential beneficial effects on public health. In vitro experiments using bovine peripheral blood mononuclear cells (PBMC), stimulated with the bacterial endotoxin lipopolysaccharide (LPS) enabled a flow cytometric assay in order to evaluate in vivo poly-ADP-ribose (PAR) levels. Results showed a significant increase of PAR after 1 h of treatment, which is consistent with the involvement of PARP activity in the inflammatory response. This study investigated PARP-1 activation in leukocyte subpopulations from bovine milk samples during udder infection. A flow cytometric assay was, therefore, performed to evaluate the PAR content in milk leukocyte subsets of cows with and without intramammary infection (IMI). Results showed that milk lymphocytes and macrophages isolated from cows with IMI had a significant increase of PAR content compared to uninfected samples. These results suggest mastitis as a new model for the study of the role of PARP in zoonotic inflammatory diseases, opening a new perspective to the "One Health" approach.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.

Differential Somatic Cell Count: Value for Udder Health Management

Intramammary infection (IMI) can cause mastitis, which is one of the costliest and most prevalent diseases in dairy cattle herds. Somatic cell count (SCC) is a well-established parameter to indicate IMI, and it represents the total count of immune cells in the milk. The differential somatic cell count (DSCC) has also long been suggested to indicate IMI, but no machine was available until recently to provide this parameter automatically. Two new machines have recently been introduced to measure the milk DSCC as an additional indicator of IMI. Here we provide insights about the DSCC measured by these two machines and the value it may provide for udder health management, based on the available literature. We also provide perspectives for future research to investigate potential value in using the DSCC to improve udder health.

Advances in Analysis of Milk Proteases Activity at Surfaces and in a Volume by Acoustic Methods

This review is focused on the application of surface and volume-sensitive acoustic methods for the detection of milk proteases such as trypsin and plasmin. While trypsin is an important protein of human milk, plasmin is a protease that plays an important role in the quality of bovine, sheep and goat milks. The increased activity of plasmin can cause an extensive cleavage of β-casein and, thus, affect the milk gelation and taste. The basic principles of surface-sensitive acoustic methods, as well as high-resolution ultrasonic spectroscopy (HR-US), are presented. The current state-of-the-art examples of the application of acoustic sensors for protease detection in real time are discussed. The application of the HR-US method for studying the kinetics of the enzyme reaction is demonstrated. The sensitivity of the acoustics biosensors and HR-US methods for protease detection are compared.

Investigation of dairy cow performance in different udder health groups defined based on a combination of somatic cell count and differential somatic cell count

Mastitis is still the costliest disease in milk production. In particular, its subclinical form, which may spread unnoticeably within a herd, is a major challenge. Somatic cell count (SCC) is broadly used as an indicator for mastitis and thus the basis for udder health management programmes, e.g. through dairy herd improvement (DHI) testing. Since recently, differential somatic cell count (DSCC, representing the combined proportion of polymorphonuclear neutrophils and lymphocytes as a percentage of total SCC) is available in addition. Our study was aimed to investigate dairy cow performance in four newly defined udder health groups (UHG) based on SCC and DSCC results from DHI testing. In total, 961,835 test-day results generated in Austria, China, Estonia, Germany, and Spain between January 2019 and March 2020 were available for data analyses. Cows were categorised into four UHG depending on test day SCC and DSCC results (UHG A: healthy/normal, ≤200,000 cells/mL and ≤65 %; B: suspicious, ≤200,000 cells/mL and >65 %; C: mastitis, >200,000 cells/mL and >65 %; D: chronic/persistent mastitis, >200,000 cells/mL and ≤65 %). Linear mixed effect models were used to compare the performance of cows between the UHG based on the parameters milk weight, energy-corrected milk, fat, protein, lactose, and estimated milk value. Highest performance was found for cows in UHG A and ranged between 21.4 (Austria) and 38.3 kg per cow and day (Spain). Interestingly, cows in group B were significantly less productive (0.9-2.4% less daily milk production) compared to those in group A. Cows in groups C (6.0-9.8% less daily production compared to group A) and D were, as expected, even less productive with a particularly significant drop for cows in group D (17.5-38.5% less daily production). These trends could be observed in all countries involved in this study. Proportions of cows in the four different UHG differed between countries, changed slightly within countries depending on season, differed depending on parity and days in milk, and were seen to vary hugely between herds. In conclusion, this study demonstrates changes in performance of dairy cows depending on their udder health status as defined based on the combination of SCC and DSCC. In particular cows in UHG B and D are of interest as they cannot be identified working with SCC only. Nevertheless, the actual udder health management measures that could be taken based on the new UHG still require further investigation.

Flow Cytometry-Detected Immunological Markers and on Farm Recorded Parameters in Composite Cow Milk as Related to Udder Health Status

Flow cytometry is a powerful technology used in many fields of cell biology. It is also used as a routine method to count somatic cells in milk and to characterize bovine milk leukocytes. In this study, we used flow cytometry to simultaneously assess the viability, the percentage of the single subsets of leukocytes and to quantify the expression of CD11b, an immunological marker of cell activation status. Immunological markers were then related with on farm recorded parameters as milk electrical conductivity (MEC) and average milk flow rate (MFR). Composite milk samples were collected from 43 cows, nine of which had naturally infected udders and 34 of which had no infected udders. First, the milk samples were classified according to bacteriological test in positive and negative. The results showed that the negative samples to bacteriological test had: (i) significantly higher percentages of live lymphocytes; (ii) significantly lower percentages of CD11b⁺ leukocytes; (iii) significantly lower MEC and higher MFR values. Then, samples were classified in three groups according to somatic cell count (SCC): Group A (n = 15), samples with SCC ≤ 100,000 cells/mL, all negative to bacteriological analysis; Group B (n = 11), samples with 100,000 < SCC < 300,000 cells/m, with four samples positive to bacteriological analysis; Group C (n = 17), samples with SCC ≥ 300,000 cell/mL with five samples positive to bacteriological analysis. Multivariate discriminant analysis was used to verify which flow cytometry immunological markers and on farm recorded parameters could better discriminate among the different groups of SCCs. Linear discriminant analysis (LDA) indicated that 5 of the 10 parameters could best be used to reveal the differences between positive and negative samples among the considered groups of SCCs. Furthermore, the Canonical discriminant analysis (CDA) indicated that composite milk samples with different SCC and infection status were clearly separated from each other in a two-dimensional space. In conclusion, the study highlighted that: (1) the conventional flow cytometry analysis applied on milk samples is a useful tool to investigate immunological parameters as potential indicators of udder health; (2) the combined evaluation of live milk leukocytes and recorded farm parameters could be useful to assess udder health status in dairy cows. The results obtained from this pilot study on few data require new and larger trials to be confirmed.

Evaluation of the new differential somatic cell count parameter as a rapid and inexpensive supplementary tool for udder health management through regular milk recording

Mastitis, particularly in its subclinical form, is the costliest disease in milk production causing substantial financial losses to the dairy industry, impairing animal welfare, and one of the main reasons for treating dairy cows with antimicrobials. Somatic cell count (SCC) is broadly used as an indicator for mastitis or intramammary infection (IMI) and is the basis for udder health management programmes, e.g., through monthly dairy herd improvement (DHI) testing. While SCC shows the total number of cells in milk, the new Differential SCC (DSCC) shows also the combined proportion of polymorphonuclear neutrophils (PMN) and lymphocytes as a percentage of the total SCC. In this study, we investigated the test characteristics of DSCC as a new supplementary indicator for mastitis screening. We collaborated with 11 herds totalling 969 dairy cows and collected metered DHI samples once a month over four months. The IMI status was assessed through analysis of aseptic composite hand-stripped samples using culture and followed by species identification using MALDI-ToF. The pathogens detected were categorised as 'no', 'minor', 'major', or 'other' pathogens. The results of our study showed that the DSCC parameter was significantly associated with the IMI status and the cow's parity but not with days in milk or test-day milk weight. On the other hand, SCC was associated with all these four factors. DSCC counts were significantly higher in samples of cows with IMI caused by major pathogens as compared to cows with no IMI or IMI by minor or other pathogens. SCC alone, DSCC alone, and the combination of DSCC and SCC were further compared based on test characteristics using exemplary cut-offs. For example, working with a cut-off of 200,000 cells/ for SCC alone compared to working with the combination of DSCC of 65 % and/or 200,000 cells/mL to classify cows as infected by major pathogens, the sensitivity increased from 78 % to 92 % and the specificity decreased from 87 % to 66 %. With the combination, the positive predictive value changed from 52 % to 34 %, and the negative predictive value stayed at the same level (96 % vs 98 %). In summary, our study provides first insights on test characteristics of the DSCC parameter used in combination with the well-established SCC for monitoring udder health using DHI testing. This combination opens up the possibility to further improve udder health monitoring programmes (e.g., improved identification of IMI caused by major pathogens) but more work on the subject is needed.

Factors Affecting the Patterns of Total Amount and Proportions of Leukocytes in Bovine Milk

Differential leukocyte count (DSCC) in milk is considered important to improve knowledge of udder immune response. The investigations on milk DSCC were limited by the techniques available until recently, when a high-throughput tool to perform DSCC opened the way to explore these factors in rapid and economically sustainable ways. We hypothesized that DSCC alone does not fully describe the pattern of these cells, since the total amount is also influenced by milk yield and SCC. Therefore, this study was designed to describe DSCC and total amount of different leukocytes in milk during the course of lactation in cows differing in parity and in levels of SCC. This study considered 17,939 individual milk tests from 12 dairy herds in Lombardy Region, where DCC testing was applied in the period of February 2018-December 2019 (23 months). The samples were divided into two subsets-"healthy" (HS) with SCC ≤200,000 cells/mL and "inflamed" (IS) with SCC >200,000 cells/mL. Cow in HS have a P + LT average between 5.0 × 108 and 3.0 × 109 cells. In IS cows, the values were 1.6 × 1010 and 2.5 × 1010. Therefore, the presence of a well-defined inflammatory process increased the overall amount of polymorphonuclear neutrophils (PMN) and lymphocytes (LYM) of 1 log, from 1 × 109 to 1 × 1010. The assessment of the total amount of PMN and LYM, to our knowledge, have never been reported in scientific literature; the values observed may be proposed as benchmarks for studies on udder immune response. When data were analyzed by days in milk (DIM), they showed that cows in first and second lactation have a significantly lower amount of PMN + LYM, when compared to cows in third and higher lactation. However, these differences are numerically not very large (7%), and suggest that, in healthy animals, the number of immune cells is kept as constant as possible. In IS, the analysis of trends based on DIM showed that both DSCC and P + LT have a significant negative trend. These data suggest that only in this group, the presence of high SCC as lactation proceeds is associated with a progressive increase in the number of macrophages. To the best of our knowledge, this is the first study describing the pattern of DSCC and the total amount of PMN + LYM in relation to parity, days in milk, and SCC, and it may be considered as the first contribution in the investigation on mammary gland immune response by the means of differential cell counts in milk.

Differential Somatic Cell Count as a Novel Indicator of Milk Quality in Dairy Cows

Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.

Differential Somatic Cell Count as a Marker for Changes of Milk Composition in Cows with Very Low Somatic Cell Count

Simple Summary

Recently, the availability of a high-throughput milk analyzer performing a partial differential somatic cell count (DSCC) opened new opportunities in investigations on bovine udder health. The information supplied by this new tool would be of importance in cows with a very low somatic cell count (SCC ≤ 50,000 cells/mL). Our investigation confirmed that the repeatability of the measurement allows its use under field conditions. The observational data did not find an association between DSCC and intramammary infections in very low SCC cows. However, our data showed that all the major milk components decreased as the DSCC was raised. These findings confirmed that DSCC could be a new informative tool for dairy farmers to monitor the changes in milk quality. DSCC may be suggested as a marker to identify early changes in milk composition, as a result of an alteration in milk secretion mechanisms.

Abstract

The recent availability of a high-throughput milk analyzer performing a partial differential somatic cell count (DSCC) opened new opportunities in investigations on bovine udder health. This analyzer has a potential limitation on the accuracy of measurements when the somatic cell count (SCC) is below 50,000 cells/mL, values characterizing a good proportion of lactating cows in many herds. We obtained data for cows below this threshold, assessed the repeatability of these measurements and investigated the relationship between DSCC and udder health, milk composition and yield. Overall, 3022 cow milk test records performed on a Fossomatic™ 7/DC (Foss A/S, Hillerød, Denmark) were considered; 901 of them had an SCC ≤ 50,000 cells/mL. These latter samples were analyzed by qPCR to identify the presence of bacteria. Overall, 20.75% of the samples (187) were positive. However, the health status did not have any significant association with DSCC. The analysis of the association of DSCC on milk fat, protein and casein showed a significant decrease in their proportions as the DSCC increased, whereas it was not observed for milk yield and lactose. Therefore, DSCC in very low SCC cows may be suggested as a marker to identify early changes in milk composition.

Immune response in nonspecific mastitis: What can it tell us?

We analyzed a large number of immune response parameters from quarter milk samples with distinct bacteriological and quarter somatic cell count (qSCC) statuses. Furthermore, we sought to explore and identify displayed immune response patterns in milk samples from mammary glands with nonspecific mastitis. Thus, 92 quarter milk samples from 28 cows were stratified into 4 groups, as follows: (1) 49 culture-negative control quarters with a low qSCC (<1 × 10⁵ cells/mL) from 19 dairy cows (so-called healthy quarters); (2) 15 culture-negative quarters with high qSCC (>2 × 10⁵ cells/mL; so-called quarters with nonspecific mastitis) from 10 dairy cows; (3) 8 culture-positive quarters with low qSCC (noninflammatory quarters with low qSCC) from 5 dairy cows; and (4) 20 culture-positive quarters with high qSCC (so-called truly infected quarters) from 8 dairy cows. Using flow cytometry, we evaluated the percentage of milk neutrophils and their viability, intracellular reactive oxygen species production, phagocytosis, and the expression of CD62L, CD11b, and CD44 for each of the 4 quarter strata. Furthermore, the percentage of monocyte/macrophages, B cells, and T lymphocyte subsets were evaluated by flow cytometry. Milk samples from bacteriologically negative quarters (both with a low and elevated qSCC) had a lower qSCC than those with bacteriologically positive outcomes (both with a low and elevated qSCC). As expected, the healthy quarters showed the lowest percentage of neutrophils and also showed a higher percentage of milk monocytes/macrophages and lower percentage of T lymphocytes than truly infected quarters. The most prominent result of the present study is that quarters with nonspecific mastitis showed the highest percentage of milk CD4⁺ T lymphocytes. The healthy quarters had a lower percentage of apoptotic neutrophils than noninflammatory and truly infected quarters, although it did not differ from those from the quarters with nonspecific mastitis. Our study supports the role of differential cell counting in the diagnosis of mastitis, as the milk leukocyte populations markedly fluctuate under healthy and inflammatory conditions. Furthermore, an increase in milk CD4⁺ T cells was associated with nonspecific mastitis, suggesting an increase in this leukocyte subpopulation is correlated with low bacterial shedding. Our study allows us to go further in our understanding of mammary gland immunity, providing further insights on potential protective mammary gland immunity, which we hypothesize can open new avenues for the development of novel targets that can promote bovine udder health.

Differential somatic cell count as an additional indicator for intramammary infections in dairy cows

Mastitis, often caused by intramammary infection (IMI), is a significant problem in dairy farming globally. Somatic cell count (SCC) is widely used as a parameter for screening IMI in cows that are then treated or culled. We investigated the potential of a new parameter, differential SCC (DSCC), to detect IMI at cow level when SCC is already known. We achieved this using bacterial culture (BC) and PCR to detect 4 categories of pathogens (major, minor, other, and any) in 2 Danish dairy herds. Quarter milk samples were collected from monthly dairy herd improvement samplings over 1 yr and analyzed with BC, whereas cow-level dairy herd improvement samples were analyzed using PCR. Days in milk, parity, and IMI status had a significant effect on DSCC. Using DSCC in addition to SCC significantly improved the indication of IMI compared with using only SCC in the any pathogen category in both herds as well as the minor pathogens category in herd 2 when BC was used for detection. When PCR was used to detect IMI, the use of DSCC in addition to SCC was significant for the other pathogens category in herd 1 and the minor pathogens category in herd 2. Thus, our data revealed that DSCC can add significant information describing IMI status even when SCC is already known; however, this depends on the causative pathogen. Future studies may address how to use DSCC in practice as well as consider the availability of temporal data to potentially gain insight into the course of infection.

Investigation of differential somatic cell count as a potential new supplementary indicator to somatic cell count for identification of intramammary infection in dairy cows at the end of the lactation period

The objective of this study was to investigate the new differential somatic cell count (DSCC) as a supplementary indicator to SCC for the identification of intramammary infection (IMI) in dairy cows at the end of the lactation period. Different approaches for identification of cows with IMI (i.e. often based on SCC) and targeted antimicrobial treatment of those rather than of all cows have been developed (i.e. selective dry cow treatment). Recently, DSCC representing the proportion of polymorphonuclear neutrophils and lymphocytes, has been introduced as an additional indicator for the presence of IMI. We used the last dairy herd improvement (DHI) samples taken within 42 d prior to dry-off as well as hand-stripped samples collected within 5 days prior to dry-off to measure DSCC and SCC. The bacteriological status was determined using quarter foremilk samples collected close to drying off. In total, 582 cows were dried off during our study but not all of them could be included in the data analysis for different reasons (e.g. incomplete data, samples too old for reliable determination of SCC and DSCC, contamination). Eventually, the final data set comprised of 310 cows of which 64 and 149 were infected with major and minor pathogens, respectively, and 97 were uninfected. The area under receiver-operating characteristics curves (AUC) were calculated to compare the diagnostic abilities of the different parameters. The AUC for identification of IMI by major pathogens when using the combination of DSCC and SCC was 0.64 compared to 0.62 for SCC alone and 0.62 for DSCC alone. The different parameters were further compared based on test characteristics and predictive values. For example, classifying cows as infected based on a cut-off of 200,000 cells/ml for SCC alone and in terms of using DSCC combined with SCC based on either >60% and/or >200,000 cells/ml, the sensitivity changed from 47 to 66% and the specificity from 74 to 54%. At the same time, the negative predictive value changed from 84 to 86% and the positive predictive value from 32 to 27%. Test characteristics and predictive values of the parameters DSCC and SCC were similar using DHI and hand-stripped samples. In conclusion, our study provides first indications on test characteristics and predictive values for the combination of DSCC and SCC. However, more work on this subject and the actual practical application is needed.

Analysis of milk leukocyte differential measures for use in management practices for decreased mastitis incidence

The aim of this study was to assess the usefulness of measures derived from milk leukocyte differential (MLD) in practices that improve fresh cow mastitis monitoring and decrease mastitis incidence. Quarter milk samples were collected from Holstein and Jersey cows on d 4 and 11 postcalving. Samples were analyzed using MLD, whereby cell counts and quarter infection diagnosis were obtained. Measures derived from MLD included cell scores (total leukocyte, neutrophil, macrophage, and lymphocyte scores), cell proportions (neutrophil, macrophage, and lymphocyte percentages), cell thresholds (total leukocyte, neutrophil, macrophage, and lymphocyte thresholds), and MLD diagnosis at different threshold settings (A, B, and C). Microbiological culturing of milk samples was used to determine infection status to compare the MLD diagnosis and serve as an indicator of infection. Measures derived from the microbiological analysis included occurrence of major pathogens, minor pathogens, and infection. Data analysis was based on a linear mixed model, which was used on all measures for the estimation of the fixed effects of breed, lactation number, day of sample collection, time of sampling, and quarter location, and the random effects of animal and week of sampling. All the fixed effects studied were significant for one or more of the analyzed measures. The results of this study showed that MLD-derived measures justify further study on their use for management practices for mastitis screening and prevention in early lactation.

Assessment of Poly(ADP-ribose) Polymerase1 (PARP1) expression and activity in cells purified from blood and milk of dairy cattle

Poly(ADP-ribosyl)ation (PAR) is a post-translational protein modification catalysed by enzyme member of the poly(ADP-ribose) polymerases (PARPs) family. The activation of several PARPs is triggered by DNA strand breakage and the main PARP enzyme involved in this process is PARP1. Besides its involvement in DNA repair, PARP1 is involved in several cellular processes including transcription, epigenetics, chromatin re-modelling as well as in the maintenance of genomic stability. Moreover, several studies in human and animal models showed PARP1 activation in various inflammatory disorders. The aims of the study were (1) to characterize PARP1 expression in bovine peripheral blood mononuclear cells (PBMC) and (2) to evaluate PAR levels as a potential inflammatory marker in cells isolated from blood and milk samples following different types of infection, including mastitis. Our results show that (i) bovine PBMC express PARP1; (ii) lymphocytes exhibit higher expression of PARP1 than monocytes; (iii) PARP1 and PAR levels were higher in circulating PBMCs of infected cows; (iv) PAR levels were higher in cells isolated from milk with higher Somatic Cell Counts (SCC > 100,000 cells/mL) than in cells from milk with low SCCs. In conclusion, these findings suggest that PARP1 is activated during mastitis, which may prove to be a useful biomarker of mastitis.

Relationships among quarter milk leukocyte proportions and cow and quarter-level variables under different intramammary infection statuses

The use of milk leukocyte differential (MLD) test has been proposed as a complement to somatic cell count (SCC) to assess the presence and the severity of intramammary infection. However, detailed information regarding the behavior of MLD under different physiological or pathological stages of the cow is nonexistent. The objective was to analyze the association between milk leukocyte proportions provided by a commercial automated MLD test and multiple cow and quarter-level variables. The study population consisted of 104 Holstein cows (32 primiparous and 72 multiparous) in one farm. Cows were categorized by days in milk as early (<50 DIM; n=29), middle (50–250 DIM; n=25), and late lactation (>250 DIM; n = 50). Milk from 416 quarters was collected and analyzed for lymphocytes (LYM), neutrophils (NEU), and macrophages (MAC) counts using an automated milk fluorescence microscopy system. Concurrently, a sterile composite milk sample was collected from each cow for pathogen identification through microbiological culture. Culture results were classified as no growth (NOG), gram-negative (GN), gram-positive (GP), or other (OTH). Milk leukocyte proportions varied depending on the level of total leukocyte counts (TLC; P < 0.001). Similarly, leukocyte ratios (NEU:LYM, NEU:MAC, and phagocyte:LYM) were different for multiple TLC categories (P < 0.05). There was no association between parity number and MLD; however, cows in early lactation had the greatest proportions of NEU and LYM. Leukocyte ratios varied depending on parity number and stage of lactation. Cows in the medium milk-yield category had the smallest proportions of NEU and LYM, and there was significant variation in leukocyte ratios, depending on the level of milk yield. In healthy quarters, MLD were not associated with quarter position; however, the NEU:MAC ratio was greater in rear quarters than in front quarters. In quarters with TLC >100,000, NEU% was greater in rear quarters than in front quarters (P = 0.03). For quarters with pathogen growth, TLC was greatest for GN followed by OTH and GP (P < 0.001). Milk LD depended on the isolated pathogen group, although the magnitudes of the differences were small. Although the changes in the proportions of leukocytes in milk were associated with categories of TLC, levels of milk yield, and mastitis-causing pathogen groups, the deviations were small in magnitude. Additional research is necessary to determine the potential applications for this methodology.

Estudo comparativo das diferentes técnicas empregadas na contagem diferencial de leucócitos no leite

RESUMO: A contagem de células somáticas (CCS) é um parâmetro amplamente utilizado para monitorar a saúde do úbere e a qualidade do leite, porém não diferencia as distintas populações leucocitárias. Portanto, a diferenciação das populações celulares no leite pode aprimorar o diagnóstico da mastite bovina. Dessa forma, o objetivo do presente trabalho foi avaliar as diferentes técnicas de contagem diferencial de leucócitos no leite para diagnosticar precisamente a mastite. Para tal, foram utilizadas 31 vacas da raça holandesa preta e branca em lactação (124 quartos mamários). Foram empregadas a contagem automática de células somáticas, e a contagem diferencial de leucócitos pelas técnicas de citocentrifugação, contagem diferencial de leucócitos por esfregaço direto, e citometria de fluxo com a utilização de anticorpos monoclonais específicos para identificação de cada população leucocitária. Os resultados demonstraram correlação positiva e significativa entre a proporção de leucócitos polimorfonucleares pelas diferentes técnicas e a contagem automática de células somáticas, sendo observada uma correlação discretamente mais forte com a citometria de fluxo. Além disso, foi demonstrado que os macrófagos são a população predominante no leite oriundo de glândula mamária com baixa CCS. Observaram-se também diferenças na proporção das distintas populações leucocitárias entre as distintas técnicas, resultado da possível subjetividade do examinador na contagem diferencial de leucócitos pelas técnicas de citocentrifugação e contagem microscópica direta por esfregaços, o que reforça que a citometria de fluxo pode ser uma ferramenta confiável no controle e diagnóstico da mastite.

Risk factors of teat-end hyperkeratosis and its association with udder health in dairy ewes

This study tested the hypotheses that machine milked dairy sheep have a high prevalence of teat-end hyperkeratosis (TEH), which contributes to udder health problems. A random sample of 1360 milking ewes from 28 dairy sheep farms was monitored. Milking procedures, milking parlour characteristics and maintenance were recorded during a designated on farm audit; records were obtained through observations and interviews with farmers. Number of ewes/milker, ewes/milking unit and milkings/milking unit were calculated. Vacuum level, pulsation rate and ratio were measured. Four combinations of vacuum level and pulsation rate were defined; <40 kPa and <150 cycles/min (VP1), <40 kPa and ≥150 cycles/min (VP2), ≥40 kPa and <150 cycles/min (VP3), ≥40 kPa and ≥150 cycles/min (VP4). California Mastitis Test (CMT; scores 0–4) was done on all ewes. Then the udder of each ewe was assessed for TEH (scores 1–4) and ewes were assigned into three groups according to TEH severity (no or mild, medium and severe TEH). Severe TEH (scores 3 and 4) prevalence at teat-level was ca. 13%. TEH severity was associated with the combination of vacuum level and pulsation rate; ewes milked with VP4 combination were more likely to have a one-level increase on TEH severity compared to ewes milked with VP2 and VP3 combinations. More ewes/milker and less ewes/milking unit increased the likelihood of a one-level increase on TEH severity. Finally, ewes with severe TEH were more likely to have a one-level increase on CMT score. Therefore, our hypotheses that TEH is prevalent in dairy ewes and contributes to udder health problems were confirmed. Additionally, farmers can reduce TEH prevalence by optimising the way they milk and their milking parlour.

Evaluation of effects of Mycoplasma mastitis on milk composition in dairy cattle from South Australia

BACKGROUND

Mycoplasma mastitis is increasingly posing significant impact on dairy industry. Although the effects of major conventional mastitis pathogens on milk components has been widely addressed in the literature, limited data on the effects of different Mycoplasma and Acholeplasma spp. on milk quality and quantity is available. The aim of this study was to determine the casual relationship of Mycoplasma spp. and A. laidlawii to mastitis and compare them to subclinical mastitis caused by conventional mastitis pathogens from a single dairy herd in South Australia; Mycoplasma spp. and A. laidlawii were detected using PCR applied directly to milk samples. The herd had mastitis problem with high somatic cell count and low response rate to conventional antimicrobial therapy. A total of 288 cow-level milk samples were collected aseptically and used in this study.

RESULTS

Conventional culture showed a predominance of coagulase-negative staphylococci, followed by coagulase-positive staphylococci, Streptococcus spp., Enterococcus spp., E. coli, and Klebsiella spp. PCR results showed a high prevalence of mycoplasmas (76.7%), including A. laidlawii (10.8%), M. bovis (6.2%), M. bovirhinis (5.6%), M. arginini (2%), and (52.1%) of cows were co-infected with two or more Mycoplasma and Acholeplasma species. Mycoplasma co-infection significantly increased somatic cell counts (SCC) similar to conventional mastitis pathogens and compared to non-infected cows with 389.3, 550.3 and 67.3 respectively; and decreased the milk yield with 29.0, 29.9 and 34.4 l, respectively. Mycoplasma co-infection caused significant increase in protein percentage, and significant decrease in fat percentage and total milk solids, similar to other conventional mastitis pathogens. In contrast, changes in milk composition and yield caused by various individual Mycoplasma species were non-significant.

CONCLUSIONS

Mycoplasma mastitis had on-farm economic consequences similar to common conventional mastitis pathogens. Results of our study indicate that co-infection Mycoplasma mastitis caused similar effect on milk composition to other mastitis pathogens and we hope these findings raise the awareness of the importance of their detection on routine diagnostic panels.