Readily usable strategies to control mastitis for production augmentation in dairy cattle: A review

Mastitis in dairy cattle is the most common management disorder that causes higher economic losses by lowering production and quality of milk leads to substantial economical loss. The aim of this article was to review worldwide important advances in strategies to control mastitis for production augmentation in dairy cattle. Many scientists worked to identify effective strategies to control mastitis caused by Streptococcus agalactiae, Staphylococcus aureus, and others. It is necessary to identify mechanisms of infection, define clinical and subclinical states of disease, determine exposure time, and identify pathogen-specific characteristics. Evolvement of management strategies that incorporated hygienic procedures (animal, floor, and milkman), post milking standing period of animal and strategic use of antibiotic or herbal therapy at dry-off, nutritional supplementation, fly control, body condition score optimization, etc., resulted in widespread control of mastitis. The udder, teat of animal, scientific management of milking, automatic milking procedure, genetic selection are considered as important factors to control mastitis. As farm management changed, scientists were directed to redefine control of mastitis caused by opportunistic pathogens of environmental sources and have sought to explore management strategies which will maintain animal well-being in a judicial way. Although significant advances in mastitis management have been made changing herd structure, changing climatic scenario and more rigorous milk processing standards ensure that mastitis will remain important issue for future research.

A genetic study of new udder health indicator traits with data from automatic milking systems

The current study aimed to investigate new udder health traits based on data from automatic milking systems (AMS) for use in routine genetic evaluations. Data were from 77 commercial herds; out of these, 24 had equipment for measuring online cell count (OCC), whereas all had data on electrical conductivity (EC). A total of 4,714 Norwegian Red dairy cows and 2,363,928 milkings were included in the genetic analyses. Electrical conductivity was available on quarter level for each milking, whereas OCC was measured per milking. The AMS traits analyzed were log-transformed online cell count (lnOCC), maximum conductivity (ECmax), mean conductivity (ECmean), elevated mastitis risk (EMR), and log-transformed EMR (lnEMR). In addition, lactation mean somatic cell score (LSCS) was collected from the Norwegian dairy herd recording system. Elevated mastitis risk expresses the probability of a cow having mastitis and was calculated from smoothed lnOCC values according to individual trend and level of the OCC curve. The udder health traits from AMS were analyzed as repeated milkings from 30 to 320 DIM, and LSCS as repeated parities. In addition, both ECmax and lnOCC were analyzed as multiple traits by splitting the lactation into 5 periods. (Co)variance components were estimated from bivariate mixed linear animal models, and investigated traits showed genetic variation. Estimated heritabilities of ECmean, ECmax, and lnEMR were 0.35, 0.23, and 0.12, respectively, whereas EMR and lnOCC both showed heritabilities of 0.09. Heritability varied between periods of lactation, from 0.04 to 0.13 for lnOCC and from 0.12 to 0.27 for ECmax, although standard errors of certain periods were large. Genetic correlations among the AMS traits ranged from 0 to 0.99. The genetic correlations between EC-based traits and OCC-based traits in AMS were 0. Genetic correlations with LSCS were favorable, ranging from 0.37 to 0.80 (±0.11-0.22). The strongest correlation (0.80 ± 0.13) was found between LSCS and lnEMR. Results question the value of ECmax and ECmean as indicators of udder health in genetic evaluations and suggest OCC to be more valuable in this manner. This study demonstrates a potential of using AMS data as additional information on udder health for genetic evaluations, although further investigation is recommended before these traits can be implemented.

Factors associated with milking-to-milking variability in somatic cell counts from healthy cows in an automatic milking system

Fully automated on-line analysis equipment is available for analysis of somatic cell count (SCC) at every milking in automatic milking systems. In addition to results from on-line cell counters (OCC), an array of additional cow-level and quarter-level factors considered important for udder health are recorded in these systems. However, the amount of variability in SCC that can be explained by available data is unknown, and so is the proportion of the variability that may be due to physiological or normal variability. Our aim was to increase our knowledge on OCC as an indicator for disturbances in udder health by assessing the variability in OCC in cows free from clinical mastitis. The first objective was to evaluate how much of the variability in OCC could be explained by different potential sources of variability, including intramammary infection (IMI) status (assessed by bacterial culture of quarter milk samples). The second objective was to evaluate the repeatability of the OCC sensor used in our study and the agreement between OCC values and SCC measured in a dairy herd improvement (DHI) laboratory. A longitudinal study was performed in the research herd of the Norwegian University of Life Sciences from January 5th 2016 to May 22nd 2017. Data from 62,471 milkings from 173 lactations in 129 cows were analyzed. We used ln-transformed OCC values (in 1000 cells/ml) as the outcome (lnOCC) in linear mixed models, with random intercepts at cow-level and lactation-level within cow. We were able to explain 15.0% of the variability in lnOCC with the following fixed effects: lactation stage, parity, milk yield, OCC in residual milk from the previous milking, inter-quarter difference between the highest and lowest conductivity, season, IMI status, and genetic lineage. When including the random intercepts, the degree of explanation was 55.2%. The individual variables explained only a small part of the total variability in lnOCC. We concluded that physiological or normal variability is probably responsible for a large part of the overall variability in OCC in cows without clinical mastitis. This is important to consider when using OCC data for research purposes or in decision-support tools. Sensor repeatability was evaluated by analyzing milk from the same sample multiple times. The coefficient of variation was 0.11 at an OCC level relevant for detection of subclinical mastitis. The agreement study showed a concordance correlation coefficient of 0.82 when comparing results from the OCC with results from a DHI laboratory.

A 100-Year Review: Mastitis detection, management, and prevention

Mastitis is the most frequent disease of dairy cows and has well-recognized detrimental effects on animal wellbeing and dairy farm profitability. Since the beginning of modern dairy farming, producers have sought effective methods to minimize the occurrence of mastitis in their herds. The objective of this paper is to review and highlight important advances in detection, management, and prevention of mastitis that have occurred since the first volume of the Journal of Dairy Science was published in 1917. Initial research efforts were directed at understanding the nature of pathogenic bacteria that were responsible for most intramammary infections. For decades, researchers worked to identify effective strategies to control mastitis caused by Streptococcus agalactiae and Staphylococcus aureus. To develop successful control programs, mastitis workers first had to identify mechanisms of infection, define the clinical and subclinical states of the disease, discover appropriate screening tests, determine likely points of exposure, identify pathogen-specific characteristics, and develop effective procedures for machine milking. Pioneering researchers eventually recognized that mastitis control was based on preventing new infections from occurring in healthy cows and reducing the duration that cows remained infected. Development of a control program that incorporated post-milking teat dipping, hygienic milking procedures, and strategic use of antibiotic therapy at dry-off resulted in widespread control of contagious pathogens. As herd management changed, researchers were tasked with defining control of mastitis caused by opportunistic pathogens originating from environmental sources. As mastitis pathogens have evolved, researchers have sought to define antimicrobial usage that will maintain animal wellbeing while minimizing unnecessary usage. During the last century, tremendous significant advances in mastitis control have been made but changing herd structure and more rigorous processor standards ensure that mastitis will remain an important subject focus of future research.

Genetic trends for fertility, udder health and protein yield in Swedish red cattle estimated with different models

The aim of this study was to estimate and compare genetic trends in Swedish Red cattle using a full multiple-trait (MT) model and trait-group-wise models for female fertility, udder health and protein yield. Field data for maiden heifers from 1989 and cows with a first and second lactation between 1990 and 2007 were included. (Co)variance components were estimated prior to prediction of breeding values. The estimated genetic trends were clearly favourable for protein yield and udder conformation, and in most cases neutral to favourable for clinical mastitis and calving to first insemination. In maiden heifers, the trends were neutral for number of inseminations per service period. Unfavourable genetic trends were estimated for number of inseminations in the first two lactations, but the trends seemed less unfavourable from evaluations within trait groups compared with when using the full MT model. Excluding maiden heifer data affected genetic trends less than using trait-group-wise analyses instead of a full MT model. Unfavourable genetic trends in functional traits may be missed unless the traits are evaluated in a MT model including traits under strong selection.

Estudo longitudinal da mastite subclínica e produção de leite em um rebanho mestiço Holandês-Zebu criado em sistema semi-intensivo

Acompanhou-se durante 15 meses um rebanho leiteiro, composto por diferentes graus de sangue Holandês-Zebu (HZ), em sistema semi-intensivo. Objetivou-se avaliar o comportamento longitudinal da contagem de células somáticas (CCS) e a influência da mastite subclínica (MS) na produção total e no pico de produção de leite de vacas mestiças HZ. Inicialmente, coletaram-se amostras de leite individual para análise microbiológica, a fim de identificar o perfil de patógenos causadores de mastite. Realizou-se mensalmente a CCS com o intuito de monitorar a MS. Semanalmente, avaliou-se a produção de leite. Para avaliar o efeito da CCS sobre a produção de leite, as vacas foram divididas em dois grupos, <200.000 e ≥200.000 células/mL. Os patógenos encontrados foram Streptococcusambientais (34%), células leveduriformes (29%), Staphylococcuscoagulase negativa (31%) e Staphylococcus aureus (6%), com CCS de 1.100.000, 845.000, 275.000 e 620.000, respectivamente. A CCS média variou de 255.000 a 975.000 cél./mL, com prevalência média de 42% de MS. Vacas primíparas com MS apresentaram redução da produção total de leite quando comparadas às primíparas sem MS (P<0,05). Em contraste, a produção total das vacas multíparas não foi alterada. Não foram observadas diferenças entre a CCS, a produção total e o pico de produção nos diferentes graus de sangue HZ (P>0,05). A CCS das vacas diferiu (P<0,01) entre a secagem e o pós-parto imediato. A manutenção das condições de elevado risco ambiental em rebanho leiteiro manejado em sistema semi-intensivo pode minimizar as variações na ocorrência de MS nos períodos de verão e inverno, possibilitando a expressão do problema em vacas de diferentes graus de sangue HZ. Em um rebanho caracterizado pela ocorrência de mastite predominantemente ambiental, a produção de leite na lactação total de vacas primíparas com CCS superior a 200.000 cél./mL é reduzida em comparação com vacas com CCS inferior a 200.000 cél./mL, o que não foi observado em vacas multíparas.

Estimation of Genetic Parameters for Somatic Cell Scores of Holsteins Using Multi-trait Lactation Models in Korea

The study was conducted to analyze the genetic parameters of somatic cell score (SCS) of Holstein cows, which is an important indicator to udder health. Test-day records of somatic cell counts (SCC) of 305-day lactation design from first to fifth lactations were collected on Holsteins in Korea during 2000 to 2012. Records of animals within 18 to 42 months, 30 to 54 months, 42 to 66 months, 54 to 78 months, and 66 to 90 months of age at the first, second, third, fourth and fifth parities were analyzed, respectively. Somatic cell scores were calculated, and adjusted for lactation production stages by Wilmink's function. Lactation averages of SCS (LSCS1 through LSCS5) were derived by further adjustments of each test-day SCS for five age groups in particular lactations. Two datasets were prepared through restrictions on number of sires/herd and dams/herd, progenies/sire, and number of parities/cow to reduce data size and attain better relationships among animals. All LSCS traits were treated as individual trait and, analyzed through multiple-trait sire models and single trait animal models via VCE 6.0 software package. Herd-year was fitted as a random effect. Age at calving was regressed as a fixed covariate. The mean LSCS of five lactations were between 3.507 and 4.322 that corresponded to a SCC range between 71,000 and 125,000 cells/mL; with coefficient of variation from 28.2% to 29.9%. Heritability estimates from sire models were within the range of 0.10 to 0.16 for all LSCS. Heritability was the highest at lactation 2 from both datasets (0.14/0.16) and lowest at lactation 5 (0.11/0.10) using sire model. Heritabilities from single trait animal model analyses were slightly higher than sire models. Genetic correlations between LSCS traits were strong (0.62 to 0.99). Very strong associations (0.96 to 0.99) were present between successive records of later lactations. Phenotypic correlations were relatively weaker (<0.55). All correlations became weaker at distant lactations. The estimated breeding values (EBVs) of LSCS traits were somewhat similar over the years for a particular lactation, but increased with lactation number increment. The lowest EBV in first lactation indicated that selection for SCS (mastitis resistance) might be better with later lactation records. It is expected that results obtained from these multi-trait lactation model analyses, being the first large scale SCS data analysis in Korea, would create a good starting step for application of advanced statistical tools for future genomic studies focusing on selection for mastitis resistance in Holsteins of Korea.

Genomic associations with somatic cell score in first-lactation Holstein cows

This genome-wide association study aimed to identify loci associated with lactation-average somatic cell score (LASCS) and the standard deviation of test-day somatic cell score (SCS-SD). It is one of the first studies to combine detailed phenotypic and genotypic cow data from research dairy herds located in different countries. The combined data set contained up to 52 individual test-days per lactation and thereby aimed to capture temporary increases in somatic cell score associated with infection. Phenotypic data for analysis consisted of 46,882 test-day records on 1,484 cows, and genotypic data consisted of 37,590 single nucleotide polymorphisms (SNP). Using an animal model, the associations between each individual SNP and the phenotypic data were estimated. To account for the risk of false positives, a false discovery rate threshold of 0.20 was set. The analyses showed that LASCS was significantly associated with a SNP on Bos taurus autosome (BTA) 4 and a SNP on BTA18. Likewise, SCS-SD was associated with this SNP on BTA18. In addition, SCS-SD significantly associated with a SNP on BTA6. Relatively few associations were found, suggesting that LASCS and SCS-SD are controlled by multiple loci distributed across the genome, each with a relatively small effect. Increased knowledge on genetic regulation of LASCS and SCS-SD may aid in identification of genes that play a role in mastitis resistance. Such knowledge helps us understand the genetic mechanisms leading to mastitis and in discovery of targets for mastitis therapeutics.

Osteopontin: an early innate immune marker of Escherichia coli mastitis harbors genetic polymorphisms with possible links with resistance to mastitis

Background

Mastitis is the most important disease in dairy cows and it causes significant lost of profit to producers. Identification of the genes, and their variants, involved in innate immune responses is essential for the understanding of this inflammatory disease and to identify potential genetic markers for resistance to mastitis. The progeny of dairy cows would benefit from receiving favourable alleles that support greater resistance to infection, thus reducing antibiotic use. This study aims to identify a key gene in the innate immune response to mastitis, led us to evaluate its genetic association with somatic cell score (SCS), which is an indicator of clinical mastitis, and to evaluate its impact on other traits related to milk production.

Results

The osteopontin transcript (SPP1) was identified in the somatic cells from cows experimentally infected with Escherichia coli. By selecting bulls with extreme estimated breeding values (EBVs) for SCS, which is an indicator of mammary gland health, four DNA polymorphisms in the SPP1 genomic sequence were found. Statistical analysis revealed that the SNP SPP1c.-1301G>A has an impact on EBV for SCS (P < 0.001) Using an allele substitution model, SPP1c.-1251C>T, SPP1c.-430G>A, and SPP1c.*40A>C have an impact on SCS whereas SPP1c.-1301G>A has an effect on the EBVs for milk yield (second and third lactations), fat and protein percentages (all three lactations). Analysis revealed statistically significant differences between haplotype groups at a comparison-wise level with sire EBVS for SCS for the first (P = 0.012), second (P < 0.001), and third (P < 0.001) lactations.

Conclusion

This study reports the link between DNA polymorphisms of SPP1, the number of milk immune cells and, potentially, the susceptibility to mastitis. These SNPs were identified by in silico search to be located in transcription factor recognition sites which factors are presumably involved in the Th1 immune response and in the Th2 regulation pathway. Indeed, one SNP abolished the SP1 recognition site, whereas another SNP affected the transcription binding factor IKAROS. All together, these findings support the genetic potential of these variants in terms of selection for the improvement of mastitis resistance in dairy cows.