Influence of nutrient availability on in vitro growth of major bovine mastitis pathogens.

The aim of the present study was to investigate the effects of milk composition changes on the in vitro growth of bovine mastitis pathogens. Nutritional requirements of three major bovine mastitis pathogens Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Streptococcus uberis (S. uberis) were investigated in vitro. We used ultra-high temperature (UHT) treated milk with different contents of fat, protein, and carbohydrates to test the influence of the availability of various milk constituents on pathogen growth characteristics. Additionally, the bacterial growth was investigated under experimentally modified nutrient availability by dilution and subsequent supplementation with individual nutrients (carbohydrates, different nitrogen sources, minerals, and different types of B vitamins) either to milk or to a conventional medium (thioglycolate broth, TB). Varying contents of fat, protein or lactose did not affect bacterial growth with the exception of growth of S. uberis being promoted in protein-enriched milk. The addition of nutrients to diluted whole milk and TB partly revealed different effects, indicating that there are media-specific growth limiting factors after dilution. Supplementation of minerals to diluted milk did not affect growth rates of all studied bacteria. Bacterial growth in diluted whole milk was decreased by the addition of high concentrations of amino acids in S. aureus, and by urea and additional B vitamins in E. coli and S. aureus. The growth rate of S. uberis was increased by the addition of B vitamins to diluted whole milk. The present results demonstrate that growth-limiting nutrients differ among pathogen types. Because reduced bacterial growth was only shown in diluted milk or TB, it is unlikely that alterations in nutrient availability occurring as a consequence of physiological changes of milk composition in the cow's udder would directly affect the susceptibility or course of bovine mastitis.

Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and ß-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows.

Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood ß-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.