The Irish Raw Milk Microbiome Map
A study led by Dr. Min Yap reveals that the microbial composition of raw milk is significantly influenced by seasonal, geographical, and climatic factors, offering insights for predicting raw milk quality and safety.
The microbial composition of raw milk is shaped by various factors that either facilitate or hinder the proliferation of both beneficial and harmful microorganisms. Seasonal and geographical factors have been shown to influence the diversity of the raw milk microbiota, particularly in pasture-based systems, such as Ireland. A recent Teagasc study led by Dr Min Yap from Professor Paul Cotter’s lab in Moorepark, investigated the factors influencing the raw milk microbiota over a 12-month period. The study was performed in collaboration with VistaMilk SFI Research Centre and the Dairy Processing Technology Centre (DPTC; an Enterprise Ireland Technology Centre).
The study utilised a powerful technique called shotgun metagenomic sequencing, which is used to study the genetic material, particularly DNA, present in complex microbial communities. This allows us to study the diversity of microorganisms in an environment without the need to isolate individual microbes. Findings showed that although the microbial composition of raw milk is diverse, there was a core microbiota that was detected in all samples, consisting of the bacterial species Pseudomonas_E, Lactococcus, Acinetobacter and Leuconostoc. The diversity of the microbial community was strongly linked to season and location and samples from summer were the most diverse. The study also found linkages between certain groups of microorganisms, climatic factors such as air and grass temperature and the chemical composition of the milk.
This study was the first to use shotgun metagenomics sequencing to investigate the microbial community of raw milk on this scale. It contributes to our understanding of the interconnected nature of the microbial and chemical composition of raw milk and the environment/climate. These results show potential as a basis for the development of a model for the prediction of raw milk quality and safety that would be highly beneficial and useful to the dairy industry.