Relationships among somatic cell count, California mastitis test, impedance and bacteriological status of milk in goats and sheep in early lactation

The objectives of this trial were to evaluate and compare the test characteristics of a number of indirect tests of bacteriological status of the milk from goats and sheep and to assess the affect of varying levels of prevalence of infection on the performance of those tests.The somatic cell count, California mastitis test (CMT) score, electrical impedance and the bacteriological status of 220 and 262 milk samples from the glands of lactating dairy goats and sheep, respectively, were determined. The sensitivity and specificity of indirect tests in predicting the bacteriological status were compared by analyzing the areas under the receiver operating characteristic curve and calculating the likelihood ratio at various cut-off values.Bacteria were isolated from 17.7 and 4.6% of glands from goats and sheep, respectively. Somatic cell count was a better predictor of bacteriological status than either the CMT score or impedance in both goats and sheep. However, knowledge of the CMT score in both sheep and goats and the impedance in goats increases the likelihood of predicting the presence of a bacterial pathogen compared to no testing at all (P<0.05). Knowledge of the age and days postpartum of the animals at the time of testing did not increase the probability that infection status could be predicted. Variation in cut-off levels to predict infection status reported in the literature may be due to variation in the prevalence of infection in the populations studied. Use of likelihood ratio allows comparison of tests over a range of prevalence’s as likelihood ratios are independent of prevalence. The prevalence of infection within a herd should be considered when selecting a cut-off value for indirect testing for the presence of bacteria in milk of small ruminants.     

Mid-infrared prediction of lactoferrin content in bovine milk: potential indicator of mastitis

Lactoferrin (LTF) is a milk glycoprotein favorably associated with the immune system of dairy cows. Somatic cell count is often used as an indicator of mastitis in dairy cows, but knowledge on the milk LTF content could aid in mastitis detection. An inexpensive, rapid and robust method to predict milk LTF is required. The aim of this study was to develop an equation to quantify the LTF content in bovine milk using mid-infrared (MIR) spectrometry. LTF was quantified by enzyme-linked immunosorbent assay (ELISA), and all milk samples were analyzed by MIR. After discarding samples with a coefficient of variation between 2 ELISA measurements of more than 5% and the spectral outliers, the calibration set consisted of 2499 samples from Belgium (n = 110), Ireland (n = 1658) and Scotland (n = 731). Six statistical methods were evaluated to develop the LTF equation. The best method yielded a cross-validation coefficient of determination for LTF of 0.71 and a cross-validation standard error of 50.55 mg/l of milk. An external validation was undertaken using an additional dataset containing 274 Walloon samples. The validation coefficient of determination was 0.60. To assess the usefulness of the MIR predicted LTF, four logistic regressions using somatic cell score (SCS) and MIR LTF were developed to predict the presence of mastitis. The dataset used to build the logistic regressions consisted of 275 mastitis records and 13 507 MIR data collected in 18 Walloon herds. The LTF and the interaction SCS × LTF effects were significant (P < 0.001 and P = 0.02, respectively). When only the predicted LTF was included in the model, the prediction of the presence of mastitis was not accurate despite a moderate correlation between SCS and LTF (r = 0.54). The specificity and the sensitivity of models were assessed using Walloon data (i.e. internal validation) and data collected from a research herd at the University of Wisconsin – Madison (i.e. 5886 Wisconsin MIR records related to 93 mastistis events – external validation). Model specificity was better when LTF was included in the regression along with SCS when compared with SCS alone. Correct classification of non-mastitis records was 95.44% and 92.05% from Wisconsin and Walloon data, respectively. The same conclusion was formulated from the Hosmer and Lemeshow test. In conclusion, this study confirms the possibility to quantify an LTF indicator from milk MIR spectra. It suggests the usefulness of this indicator associated to SCS to detect the presence of mastitis. Moreover, the knowledge of milk LTF could also improve the milk nutritional quality.     

The analysis of disease biomarker data using a mixed hidden Markov model (Open Access publication)

A mixed hidden Markov model (HMM) was developed for predicting breeding values of a biomarker (here, somatic cell score) and the individual probabilities of health and disease (here, mastitis) based upon the measurements of the biomarker. At a first level, the unobserved disease process (Markov model) was introduced and at a second level, the measurement process was modeled, making the link between the unobserved disease states and the observed biomarker values. This hierarchical formulation allows joint estimation of the parameters of both processes. The flexibility of this approach is illustrated on the simulated data. Firstly, lactation curves for the biomarker were generated based upon published parameters (mean, variance, and probabilities of infection) for cows with known clinical conditions (health or mastitis due to Escherichia coli or Staphylococcus aureus). Next, estimation of the parameters was performed via Gibbs sampling, assuming the health status was unknown. Results from the simulations and mathematics show that the mixed HMM is appropriate to estimate the quantities of interest although the accuracy of the estimates is moderate when the prevalence of the disease is low. The paper ends with some indications for further developments of the methodology.     

Activity of biogenic silver nanoparticles against isolates of Prototheca species from bovine mastitis

Prototheca spp. cause numerous infections in a wide variety of species, including treatment-unresponsive mastitis. Thus, the search for an effective therapy is essential. Silver nanoparticles are compounds with high therapeutic potential. This study aimed to evaluate the susceptibility profile and morphological changes in Prototheca spp. treated with biogenic silver nanoparticles (Bio-AgNP). The algaecide activity was evaluated in microplates by microdilution method, resulting in a MIC₅₀ of 30 μg ml⁻¹ and a MIC₉₀ of 60 μg ml⁻¹. Scanning electron microscopy demonstrated changes in the surface of Prototheca bovis cells following treatment. The algaecide activity of Bio-AgNP suggests a therapeutic potential as a novel approach for the control of Prototheca spp. in bovine mastitis.     

克氏棒杆菌与肉芽肿性乳腺炎相关性的研究进展

克氏棒杆菌是棒杆菌属的一员，基因组序列分析显示其具有亲脂性(需要脂质)的特点。克氏棒杆菌的临床分离株几乎均来自女性患者，且主要分离自乳腺脓肿和肉芽肿性乳腺炎(granulomatous mastitis，GM)患者的病变乳房组织样本，但其在乳腺病理中的作用尚不明确。本文对克氏棒杆菌与GM相关性的研究进展进行了综述。     

Corynebacterium uberis sp. nov. frequently isolated from bovine mastitis

Several strains belonging to the genus Corynebacterium, but not to any described species of the genus were isolated from bovine mastitic milk samples over the past five years in the diagnostic unit of the University of Bern. Six of these strains (18M0132^T, 17M2518, 18M0913, 19M0083, 20M1046 and 20M1090) that were phenotypically similar were further characterized genotypically. Gram-positive coryneform rods were catalase positive, facultative anaerobe and CAMP-test negative. Whole genome sequencing and subsequent phylogenetic analysis revealed their genome size to be 2.53 Mb and their G + C content to be between 65.4 and 65.5 mol%. Digital DNA-DNA hybridisation (dDDH) showed the highest similarity of only less than 20% with Corynebacterium mastitidis and Corynebacterium frankenforstense, which indicated that the isolates belong to an undescribed Corynebacterium species. This was confirmed by studying the average nucleotide identity (ANI) where the accepted species boundary is around 95% and which ranged between 70.3% and 74.9% with the most closely related species C. mastitidis. We established MALDI-TOF fingerprints of the species, which allows a clear separation from related species and can be used by other laboratories for diagnostic purposes.Based on our analyses we conclude that the selected strains belong to a previously undescribed species and propose the name Corynebacterium uberis sp. nov. The proposed type strain is 18M0132^T (=DSM 111922^T, = CCOS 1972^T).