Leveraging community-based sequencing approaches to characterise the dairy microbiome
Microorganisms exist in communities along the food chain and contribute, positively and negatively, to the safety and quality of food products downstream. While traditional culture-based methods usually investigate specific groups of microorganisms, advances in high-throughput DNA sequencing have enabled the study of entire microbial communities in food or food-related samples. In this thesis, shotgun metagenomic sequencing was employed to investigate microbial communities in bulk tank milk. First, shotgun sequencing was used to determine the impact of farm cleaning methods on the microbiome. The results revealed that seasonality and geography significantly impacted the bulk tank milk microbiota but that the use of chlorine-based relative to chlorine-free cleaning methods did not result in differences. Next, further sampling was performed to determine if interactions exist between the bulk tank milk microbiota, raw milk chemical composition and climatic variables. Analysis of shotgun sequencing data from bulk tank milk over 12-months revealed a stable core microbiota and showed a significant and obvious influence of season and location on the raw milk microbiota. Associations were detected between pathogenic and mastitis-related taxa and chemical composition and climate/environmental variables. The interconnected nature of these variables suggests there is merit in considering the use of chemical and/or climate variables as markers for food safety and spoilage threats in bulk tank milk. While useful information can be obtained through shotgun metagenomic sequencing, the untargeted nature of this approach involves the sequencing of all DNA present in samples, including host-derived reads that are present in high proportions in milk (~90%), as well as both live and dead cells, which could alter inferred community structure or diversity. To overcome these challenges, two studies were completed to improve current shotgun metagenomic sequencing methodology. First, three methods were evaluated to assess their relative ability to deplete host DNA or enrich microbial DNA. The MolYsis™ Complete5 kit yielded significantly higher proportions of microbial reads and improved sequencing depth, allowing for further characterisation of the bovine and human milk microbiomes through the recovery of metagenome-assembled genomes (MAGs). Tackling the issue of microbial viability, 4 methods were explored to compare their relative efficacy at distinguishing between viable and non-viable cells with a five-strain live and heat-inactivated model microbial community spiked into a bovine milk matrix and sequenced on Illumina and Oxford Nanopore Technologies (ONT) platforms. The results showed that all methods were relatively accurate, but significant differences between library type (DNA and RNA) and sequencing technologies (Illumina and ONT) were found. Variations between library types were due to the differing molecular targets, while sequencing depths, error rates and bioinformatic pipelines likely contributed to the differences between sequencing technologies. This pilot study provides insights into the potential enhancement of sequencing-based approaches to better characterise and differentiate live and dead microbes in food-related environments, but more work is required to optimise these methods before more widespread use. Overall, the use of shotgun metagenomics provided valuable insights into the bulk tank raw milk microbiota, improving our current understanding of the factors that influence the quality and safety of raw milk. Building on the work performed during this thesis, further improvements can enhance existing community-based sequencing methods to allow for better understanding of food microbiomes, that in turn would be beneficial for food safety, quality, and public health.
Dairy, Microbiota, Metagenomics, High-throughput sequencing
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