Etiology and antimicrobial susceptibility of udder pathogens from cases of subclinical mastitis in dairy cows in Sweden

<p>Abstract</p> <p>Background</p> <p>A nationwide survey on the microbial etiology of cases of subclinical mastitis in dairy cows was carried out on dairy farms in Sweden. The aim was to investigate the microbial panorama and the occurrence of antimicrobial resistance. Moreover, differences between newly infected cows and chronically infected cows were investigated.</p> <p>Methods</p> <p>In total, 583 quarter milk samples were collected from 583 dairy cows at 226 dairy farms from February 2008 to February 2009. The quarter milk samples were bacteriological investigated and scored using the California Mastitis Test. Staphylococci were tested for betalactamase production and presence of resistance was evaluated in all specific udder pathogens. Differences between newly infected cows and chronically infected cows were statistically investigated using logistic regression analysis.</p> <p>Results</p> <p>The most common isolates of 590 bacteriological diagnoses were <it>Staphylococcus (S) aureus </it>(19%) and coagulase-negative staphylococci (CNS; 16%) followed by <it>Streptococcus (Str) dysgalactiae </it>(9%), <it>Str. uberis </it>(8%), <it>Escherichia (E.) coli </it>(2.9%), and <it>Streptococcus </it>spp. (1.9%). Samples with no growth or contamination constituted 22% and 18% of the diagnoses, respectively. The distribution of the most commonly isolated bacteria considering only bacteriological positive samples were: <it>S. aureus </it>- 31%, CNS - 27%, <it>Str. dysgalactiae </it>- 15%, <it>Str. uberis </it>- 14%, <it>E. coli </it>- 4.8%, and <it>Streptococcus </it>spp. - 3.1%. There was an increased risk of finding <it>S. aureus, Str. uberis </it>or <it>Str. dysgalactiae </it>in milk samples from chronically infected cows compared to findings in milk samples from newly infected cows. Four percent of the <it>S. aureus </it>isolates and 35% of the CNS isolates were resistant to penicillin G. Overall, resistance to other antimicrobials than penicillin G was uncommon.</p> <p>Conclusions</p> <p><it>Staphylococcus aureus </it>and CNS were the most frequently isolated pathogens and resistance to antimicrobials was rare.</p

Evaluation of two dairy herd reproductive performance indicators that are adjusted for voluntary waiting period

<p>Abstract</p> <p>Background</p> <p>Overall reproductive performance of dairy herds is monitored by various indicators. Most of them do not consider all eligible animals and do not consider different management strategies at farm level. This problem can be alleviated by measuring the proportion of pregnant cows by specific intervals after their calving date or after a fixed time period, such as the voluntary waiting period. The aim of this study was to evaluate two reproductive performance indicators that consider the voluntary waiting period at the herd. The two indicators were: percentage of pregnant cows in the herd after the voluntary waiting period plus 30 days (PV30) and percentage of inseminated cows in the herd after the voluntary waiting period plus 30 days (IV30). We wanted to assess how PV30 and IV30 perform in a simulation of herds with different reproductive management and physiology and to compare them to indicators of reproductive performance that do not consider the herd voluntary waiting period.</p> <p>Methods</p> <p>To evaluate the reproductive indicators we used the SimHerd-program, a stochastic simulation model, and 18 scenarios were simulated. The scenarios were designed by altering the reproductive management efficiency and the status of reproductive physiology of the herd. Logistic regression models, together with receiver operating characteristics (ROC), were used to examine how well the reproductive performance indicators could discriminate between herds of different levels of reproductive management efficiency or reproductive physiology.</p> <p>Results</p> <p>The logistic regression models with the ROC analysis showed that IV30 was the indicator that best discriminated between different levels of management efficiency followed by PV30, calving interval, 200-days not-in calf-rate (NotIC200), in calf rate at100-days (IC100) and a fertility index. For reproductive physiology the ROC analysis showed that the fertility index was the indicator that best discriminated between different levels, followed by PV30, NotIC200, IC100 and the calving interval. IV30 could not discriminate between the two levels.</p> <p>Conclusion</p> <p>PV30 is the single best performance indicator for estimating the level of both herd management efficiency and reproductive physiology followed by NotIC200 and IC100. This indicates that PV30 could be a potential candidate for inclusion in dairy herd improvement schemes.</p

Genetic and genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield, and four mastitis-related traits (milk somatic cell count, California Mastitis Test score, total viable bacterial count in milk and clinical mastitis presence) were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism (SNP) array. We performed targeted genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis traits. Environmental factors appeared to favour both milk production and udder health. There were no overlapping of SNPs associated with mastitis resistance and milk yield in Chios sheep. Furthermore, four distinct Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations other than those previously identified to affect mastitis resistance. Five genes (DNAJA1, GHR, LYPLA1, NUP35 and OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of two of these genes (NUP35 and OXCT1) was enriched in immune tissues implying a potentially pleiotropic effect or likely role in milk production during udder infection, which needs to be further elucidated in future studies. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable

Mediation analysis to estimate direct and indirect milk losses associated with bacterial load in bovine subclinical mammary infections

Milk losses associated with mastitis can be attributed to either effects of pathogens per se (i.e. direct losses) or to effects of the immune response triggered by the presence of mammary pathogens (i.e. indirect losses). Test-day milk somatic cell counts (SCC) and number of bacterial colony forming units (CFU) found in milk samples are putative measures of the level of immune response and of the bacterial load, respectively. Mediation models, in which one independent variable affects a second variable which, in turn, affects a third one, are conceivable models to estimate direct and indirect losses. Here, we evaluated the feasibility of a mediation model in which test-day SCC and milk were regressed toward bacterial CFU measured at three selected sampling dates, 1 week apart. We applied this method on cows free of clinical signs and with records on up to 3 test-days before and after the date of the first bacteriological samples. Most bacteriological cultures were negative (52.38%), others contained either staphylococci (23.08%), streptococci (9.16%), mixed bacteria (8.79%) or were contaminated (6.59%). Only losses mediated by an increase in SCC were significantly different from null. In cows with three consecutive bacteriological positive results, we estimated a decreased milk yield of 0.28 kg per day for each unit increase in log2-transformed CFU that elicited one unit increase in log2-transformed SCC. In cows with one or two bacteriological positive results, indirect milk loss was not significantly different from null although test-day milk decreased by 0.74 kg per day for each unit increase of log2-transformed SCC. These results highlight the importance of milk losses that are mediated by an increase in SCC during mammary infection and the feasibility of decomposing total milk loss into its direct and indirect components. © The Animal Consortium 201