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Intramammary infections (IMI) in sheep have a major economic impact through reduced milk production, premature culling and even death of ewes. This study hypothesizes that the sheep mammary gland could host a microbiome with certain members affecting SCC. Previous studies have been cross-sectional, using only one sample per subject and not conducted in sheep. This limits understanding causality; that is, how infection develops and what triggers development of disease. A longitudinal study of 30 sheep, each with two mammary gland halves, collected over 8 weeks, provided 379 milk samples and data on ewe parity and milk SCC. DNA was extracted from milk samples and processed using a bacterial 16S rRNA gene targeted PCR. Bacterial community diversity was visualised using denaturing gradient gel electrophoresis (DGGE). DGGE fingerprints were analysed in a mixed effects regression model to identify associations between individual DGGE bands and changes in SCC. Those bands associated with SCC were sequenced. Corynebacterium efficiens, Psychrobacter maritimus, Streptococcus uberis, Burkholderia cepacia, Fusobacterium necrophorum, Trueperella pyogenes, Pseudomonas chlororaphis and Psychrobacter faecalis were significantly associated with a higher SCC. Achromobacter xylosoxidans, Nocardia globerula or Rhodococcus qingshengii, Atopostipes suicloacalis, Mannheimia haemolytica, Jeotgalicoccus psychrophilus and Sharpea azabuensis were significantly associated with a lower SCC. A protocol to analyse all study samples using Illumina MiSeq sequencing was developed to elucidate the complex interactions between the sheep mammary gland microbiome and SCC. The DGGE and MiSeq results show a persistent community has been detected over time, with similarities and differences by mammary gland half, lactation and age. Associations between individual bacterial species and SCC were identified through mixed effect modelling. The DGGE results were comparable to the MiSeq results from 5 sheep. Analysis of all 379 samples by MiSeq sequencing and mixed effects models will be used to directly test the study hypotheses.