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Despite the considerable advances that have been made to improve dairy food safety, there is rising concern that pasteurization is not sufficient for the destruction of plasmid-mediated antimicrobial resistance (AMR) genes of resistant bacteria and could stimulate bacteria to enter into a viable but nonculturable (VBNC) state. In the current study, we surveyed the prevalence of 1 genomic and 9 plasmid-mediated AMR genes in 100 samples (bulk tank milk and milk filter socks) at the farm level and 152 commercial milk samples (pasteurized and UHT milks) and assessed the VBNC state in dairy bacteria. Results revealed that sul2 was the most prevalent plasmid-mediated gene in milk filter socks (96%), bulk tank milk (48%), pasteurized milk (68%), and UHT (43%) milk; in contrast, mecA was not detected in any sample. Additionally, commercial pasteurization (as currently practiced) failed to decrease the prevalence of the bla TEM-B1 (43%), tetK (30%), and tetA (55%) plasmid-mediated AMR genes; thus, commercial pasteurization may be one of the factors creating the VBNC state in some dairy bacteria. Continued research is necessary to identify bacterial species entering the VBNC state after pasteurization, to assess their potential hazard level and shed more light on the expression and possibility of horizontal gene transfer of those plasmid-mediated AMR genes., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-scale mining of milk composition features by pattern recognition models can identify the best predictors of SCM within the milk composition features. To this end, using data mining algorithms, we conducted a large-scale and longitudinal study to evaluate the ability of various milk production parameters as indicators of SCM. SCM is the most prevalent disease of dairy cattle, causing substantial economic loss for the dairy industry. Developing new techniques to diagnose SCM in its early stages improves herd health and is of great importance. Test-day Somatic Cell Count (SCC) is the most common indicator of SCM and the primary mastitis surveillance approach worldwide. However, test-day SCC fluctuates widely between days, causing major concerns for its reliability. Consequently, there would be great benefit to identifying additional efficient indicators from large-scale and longitudinal studies. With this intent, data was collected at every milking (twice per day) for a period of 2 months from a single farm using in-line electronic equipment (346 248 records in total). The following data were analysed: milk volume, protein concentration, lactose concentration, electrical conductivity (EC), milking time and peak flow. Three SCC cut-offs were used to estimate the prevalence of SCM: Australian ≥ 250 000 cells/ml, European ≥200 000 cells/ml and New Zealand ≥ 150 000 cells/ml. At first, 10 different Attribute Weighting Algorithms (AWM) were applied to the data. In the absence of SCC, lactose concentration featured as the most important variable, followed by EC. For the first time, using attribute weighted modelling, we showed that the concentration of lactose in milk can be used as a strong indicator of SCM. The development of machine-learning expert systems using two or more milk variables (such as lactose concentration and EC) may produce a predictive pattern for early SCM detection.

Objectives: Currently, there is no consensus protocols regarding the combination of glycerol (GLY), gelatin or foetal bovine serum (FBS) with dimethyl sulphoxide (DMSO) as cryoprotectants for Mycoplasma bovis in bovine milk samples. This study aimed to compare different cryopreservation compounds and storage temperatures for M. bovis., Results: There were significant differences in the survival of M. bovis on different media. Differences were also observed between different storage conditions. All additives improved the survival of M. bovis in comparison to control (CON). The combination of GLY and DMSO was shown to be significantly different to CON with 57.1% (95% CI = 21.43-133.34) and 19.1% (95% CI = 11.73-60.27), respectively at week 16, and its use should be encouraged as a cryoprotectant for M. bovis at - 20 and - 80 °C. GEL/DMSO showed the highest survival rate for M. bovis with 57.14% (95% CI = 21.43-133.34) at 4 °C in comparison with CON 14.29% (95% CI = 9.60-50.39). FBS/DMSO showed the highest survival rate for the short-term preservation similarly to other additives. The evaluated cryopreservative compounds would improve survivability of M. bovis in milk for both transport and long-term storage. Hence, it is recommended to use the mentioned methods for routine transportation or storage purposes for suspicious M. bovis milk samples.

Objectives: This study aimed to provide a rapid, accurate and cost-effective diagnostic real time polymerase chain reaction-high resolution melting curve assay (PCR-HRM) to identify and distinguish between four different mycoplasmas and Acholeplasma laidlawii isolated at cow-level from a single commercial dairy farm in South Australia. One set of genus-level universal primers was designed targeting the 16S ribosomal RNA gene., Results: Real time PCR-HRM analysis was able to identify and distinguish between five different mollicutes, namely A. laidlawii, M. arginini, M. bovirhinis, M. bovis and uncultured Mycoplasma. Results were confirmed through sequencing. Our developed assay provides rapid and accurate screening for Mycoplasma mastitis detection.

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.

Bovine colostrum contains a high concentration of immune-related microRNAs (miRNAs) that are packaged in exosomes and are very stable. In this study, 5 immune-related miRNAs (miR-142-5p, miR-150, miR-155, miR-181a, and miR-223) were quantified in dam blood, colostrum, and calf blood using reverse transcription quantitative PCR. Their levels in calf blood after colostrum ingestion were investigated to assess whether miRNAs are transferred from the dam to newborn calves. Three groups of Holstein–Friesian bull calves were bottle-fed 2 L of colostrum or milk from different sources twice per day. The group A calves received colostrum from their own dam and the group B calves were fed foster dam colostrum. Each pair of group A and group B calves were fed identical colostrum from the same milking of the corresponding group A dam for 3 d and then bulk tank milk for 7 d after birth. Group C calves were fed only 2L of "pooled colostrum" from multiple dams d 0 to 4 postpartum, and then fed bulk tank milk thereafter for 7 d after birth. The groups were fed colostrum from different sources and different amounts to assess possible miRNA absorption from the colostrum. All miRNAs were at the highest level in colostrum at d 0 and then decreased rapidly after d 1. The level of miR-150 had the largest decrease from 489 × 106 copies/µL (d 0) to 78 × 106 copies/µL (d 1). MicroRNA-223 and miR-155 were the most abundant in both colostrum and milk. Dam colostrum had significantly higher levels of miR-142-5p, miR-155, and miR-181a than the bulk tank milk. However, only the miR-155 concentration was significantly higher in the dam colostrum than in the pooled colostrum. The concentrations of miRNAs in the colostrum were less than in the cow blood (100- to 1,000-fold less). There was no significant correlation between the level of miRNAs in the dam blood and their colostrum, suggesting that miRNA is synthesized locally by the mammary gland rather than being transferred from the blood. MicroRNA-223 had the highest level in both calf and cow blood compared with the other 4 immune-related miRNAs. Calves were born with high levels of immune-related miRNAs in their blood, and there were no significant differences in miRNA levels between the 3 calf groups at birth or after they were fed different colostrum. This suggests that these miRNAs were not transferred from the colostrum to the newborn calves. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to assess a phage‐displayed MilA protein of Myc. bovis in an indirect ELISA for the detection of Myc. bovis antibodies in milk samples. Methods and Results: The desired sequence of milA gene was synthesized and cloned into pCANTAB‐F12 phagemid vector. The expression of the MilA on the phage surface was confirmed by Western blotting. The recombinant phage was used in the development of an indirect ELISA to detect Myc. bovis antibodies in milk samples. There was a significant agreement between the results of phage‐based ELISA and recombinant GST‐MilA ELISA for the detection of Myc. bovis antibodies in milk samples. Conclusions: The inexpensive and convenient phage‐based ELISA can be used instead of recombinant protein/peptide ELISA as an initial screening of Myc. bovis‐associated mastitis. Significance and Impact of Study: Mastitis associated with Myc. bovis is a continuous and serious problem in the dairy industry. Sero‐monitoring of Myc. bovis infection cases are one of the key factors for surveillance of the infections in dairy farms. Despite the existence of some commercially serological assays for Myc. bovis antibodies, they have some limitations regarding their sensitivity and availability. The development of accurate diagnosis tools could contribute to control programmes of Myc. bovis‐associated mastitis in the dairy herds. [ABSTRACT FROM AUTHOR]

Lactoferrin (LF) is glycoprotein, which is normally excreted in cow's milk, but as a result of inflammatory processes in the mammary gland, its concentration is being increased. The aim of this research was to determinate whether the LF concentration in milk is influenced by increased number of milk somatic cell count. In this research we used milk from (n = 345) Holstein-Friesian cows in Pelagonia region, or more precisely milk from healthy (n = 112) and infected quarters (n = 233). A quarter was classified as healthy when no visible signs of mastitis were detected or the California Mastitis Test (CMT) was negative. A quarter was classified as subclinical when no visible signs of mastitis were detected but CMT was positive. A quarter was classified as clinical mastitis when there were visible signs of mastitis (cow, udder or milk appearance). The milk samples were analysed instrumentally for physico - chemical properties (Lactoscope C4+), somatic cell count (SCC) by Bentley Somacount CC 150, total number of bacteria (CFU) (by Bentley Bactocount IBC), and by ELISA for concentrations of lactoferrin. We used SPSS 15.0 for analysis of gained data. Significant differences were detected in concentrations of lactoferrin in healthy quarters (915.94 µg/mL) and in quarters with sub-clinical (2,095.87 µg/mL) and clinical mastitis (3,528.99 µg/mL) (p < 0.001). A correlation between lactoferrin and lactose (r = -0.21, p < 0.01), lactoferrin and CFU (r = 0.28, p < 0.01) as well as between lactoferrin and somatic cells (r = 0.32, p < 0.01) was observed. These results initiate that lactoferrin could be used as complementary test to somatic cell count, and potential to be a primary diagnostic test for subclinical and clinical mastitis in dairy cows. Furthermore, it could be used as natural antibiotic in treatment of mastitis in dairy cows, in order to decrease the presence of antibiotic residuals in milk, thereby to improve hygiene of raw milk. [ABSTRACT FROM AUTHOR]

The objective of this study was to detect Mycoplasma bovis specific antibodies using a recently reported MilA ELISA with the aim to detect M. bovis antibodies in milk. An indirect ELISA, based on a recombinant fragment of the Mycoplasma immunogenic lipase A (MilA) protein, was conducted on 291 milk samples for the detection of M. bovis antibodies. Samples were also tested with conventional Mycoplasma culture and M. bovis PCR. Samples were collected from individual cows from 2 commercial dairy herds in South Australia. Of 291 samples tested, 68 (23.4%) were detected positive for M. bovis antibodies, 150 (51.5%) were positive for M. bovis in PCR and 166 (57.0%) in bacterial culture. These results indicate that MilA indirect ELISA can be utilized for the detection of M. bovis antibodies in milk. [ABSTRACT FROM AUTHOR]

Simple Summary: Invisible (subclinical) mastitis decreases milk quality and production. Invisible mastitis is linked to an increased use of antimicrobials. The risk of the emergence of antimicrobial-resistant bacteria is a major public health concern worldwide. Therefore, early detection of infected cows is of great importance. Machine learning has opened a new avenue for early mastitis prediction based on simple and accessible milking parameters, such as milk volume, fat, protein, lactose, electrical conductivity (EC), milking time, and milking peak flow. However, farm heterogeneity is a major challenge where multiple patterns can predict mastitis. Here, we employed a classification based on associations and scaling approach for multiple pattern discovery over multiple years. The approach we have developed helps to address farm heterogeneity and generalise machine learning-based diagnosis of mastitis worldwide. Subclinical mastitis, an economically challenging disease of dairy cattle, is associated with an increased use of antimicrobials which reduces milk quantity and quality. It is more common than clinical mastitis and far more difficult to detect. Recently, much attention has been paid to the development of machine-learning expert systems for early detection of subclinical mastitis from milking features. However, differences between animals within a farm as well as between farms, particularly across multiple years, are major obstacles to the generalisation of machine learning models. Here, for the first time, we integrated scaling by quartiling with classification based on associations in a multi-year study to deal with farm heterogeneity by discovery of multiple patterns towards mastitis. The data were obtained from one farm comprising Holstein Friesian cows in Ongaonga, New Zealand, using an electronic automated monitoring system. The data collection was repeated annually over 3 consecutive years. Some discovered rules, such as when the milking peak flow is low, electrical conductivity (EC) of milk is low, milk lactose is low, milk fat is high, and milk volume is low, the cow has subclinical mastitis, reached high confidence (>70%) in multiple years. On averages, over 3 years, low level of milk lactose and high value of milk EC were part of 93% and 83.8% of all subclinical mastitis detecting rules, offering a reproducible pattern of subclinical mastitis detection. The scaled year-independent combinational rules provide an easy-to-apply and cost-effective machine-learning expert system for early detection of hidden mastitis using milking parameters. [ABSTRACT FROM AUTHOR]