The global market for functional foods and nutraceuticals is growing substantially, with an estimated value in excess of $100bn. The development of these products is largely dependent on identification of naturally occurring bioactive molecules. Milk is a complex food and a rich source of biologically active proteins that provide an opportunity to develop functional dairy products.
Recent advances in bovine genome sequencing, and the development of post-genomic tools, has provided a mechanism to annotate the mammary gland transcriptome and identify potential novel protein-derived milk bioactives. We surveyed gene expression profiles from dairy cow mammary tissue collected during lactation, to classify expressed genes and to evaluate the capacity to translate the findings for milk protein detection.
Expressed genes from the mammary glands of lactating dairy cows were collated by analysis of microarray data. Bovine Affymetrix Gene Chips were used to probe ~20K genes and from these a permissive set of over 4,000 were selected for further consideration. The genes were then analysed through annotation pipeline that identified gene products with putative bioactive potential. Excluding caseins, a total of 175 genes were then classified for evaluation based on physiological properties. The greatest proportion were related to immunity and defense, or digestion and metabolism.
Milk proteins were analysed for comparison with genes detected in mammary glands, and annotated as physiologically active and potential bioactives. Whey proteins were extracted from public data bases or analysed directly from a commercial source. Direct analysis was performed using a combination of chromatography, electrophoresis and mass spectrometry. This analysis identified proteins with abundance down to 3% of total whey protein. These were complemented by inclusion of more abundant proteins, and a total of 90 proteins were selected for evaluation and comparison with those annotated from expressed genes.
The comparison of 175 proteins predicted from the mammary gland gene expression data and 90 proteins from milk analysis identified 19 that were common to both sets. These were predominantly derived from abundant milk proteins but also included minor proteins or expressed The results suggest that there is some predictive value in transcriptomic-based approaches to detection of milk proteins, and that it provides a useful method for annotation. However with increased sensitivity of proteomic tools, direct approaches may provide sufficient levels of sensitivity for bioactive screening.
