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Mastitis is a disease of the mammary gland which affects most mammals and is one of the costliest ongoing challenges in modern dairy farming. The most significant challenges in mastitis management are the speed and accuracy of diagnosis and the use of antibiotics. Current mastitis diagnosis in veterinary practices in the United Kingdom utilises culture-based techniques. However, this approach has some limitations including; processing time, species selection biases and culture failure. This ongoing PhD project seeks to assess the utility of high-throughput sequencing technology in addressing the current challenges in mastitis diagnosis. Samples were obtained from cattle from farms in North Yorkshire, United Kingdom. Cattle were selected from monthly somatic cell count records as mastitis positive cases with a cell count between 250 000 and 550 000 cells ml−1 or control animals with a count below 200 000 cells. Mastitis positive cases were further split into bacteriology positive and negative groups. During sampling a cow-side somatic cell test (California Milk Test) was performed to confirm the monthly database readings. All farms sampled were conventional dairy farms with comparable management systems. Samples were collected by trained veterinarians following a pre-defined protocol designed to limit sample contamination. Microbial community diversity, richness and composition will be compared between sample groups to survey for variations which may explain why culture fails in culture negative subclinical cases. 131 sample animals have been assigned to study groups with samples collected, DNA extracted and prepared for sequencing on the Illumina MiSeq platform with results expected in January 2019.