Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk.

Somatic cell count (SCC) is associated with changes in milk composition, including changes in proteins, lipids, and milk metabolites. Somatic cell count is normally used as an indicator of mastitis infection. The compositional changes in protein and fat affect milk coagulation properties, and also the metabolite composition is thought to contribute to differential milk properties. Milk somatic cells comprise different cell types, which may contribute to differential milk metabolite fingerprints. In this study, milk from a relatively large number of individual cows, representing significant differences in SCC, were analyzed by nuclear magnetic resonance (NMR)-based metabonomics, and the milk metabolite profiles were analyzed for differences related to SCC. Global principal component analysis performed on 876 samples from 2 Danish dairy breeds and orthogonal projection of latent structures discriminant analysis performed on a smaller subset (n=70) representing high (SCC >7.2×10(5) cells/mL) and low (SCC <1.4×10(4) cells/mL) milk SCC identified latent variables, which could be attributed to milk with elevated SCC. In addition, partial least squares regression between the NMR milk metabolite profiles and SCC revealed a strong correlation. The orthogonal projection of latent structures discriminant analysis and partial least squares regressions pinpointed specific NMR spectral regions and thereby identification of milk metabolites that differed according to SCC. Relative quantification of the identified metabolites revealed that lactate, butyrate, isoleucine, acetate, and β-hydroxybutyrate were increased, whereas hippurate and fumarate were decreased in milk with high levels of somatic cells.