Variation in structure and virulence of the microbial community of sheep udders (PhD)

This is the first longitudinal microbiome study of intramammary infections in a farm animal. The data presented in the final report provides the first evidence of a microbial community in the sheep mammary gland. A persistent community was detected over time, with similarities and differences identified between sheep, mammary gland halves, over lactation and with sheep age. Associations between certain community members and mammary gland health have been identified through mixed effect modelling. Further analysis of the sequencing data produced in this project has the potential to improve our understanding of the role microbial community composition of the MG plays in IMI.

The Challenge

Mastitis is a term used to describe any swelling of the sheep udder. It is usually caused by a bacterial infection. Mastitis is a difficult disease for sheep farmers to manage partly because more than 120 different types of bacteria have been linked to mastitis.

The large number of bacteria associated with mastitis suggests that the sheep udder may be a site where bacteria live in a community. Two known examples of this in humans are in the gut and lungs. Changes in the balance of bacteria in the communities that exist in the human gut and lungs leads to infections such as gastroenteritis and pneumonia. This may be the same in sheep, whereby changes in the community of bacteria in the udder cause infections to arise.

Improving the understanding of animal-associated microbial communities (microbiomes) is essential in identifying strategies to maximise health and generate novel approaches to management of persistent bacterial infections. Intramammary infections (IMI) in sheep present as a range of scenarios from acute severe systemic clinical mastitis to subclinical infection detectable by a raised somatic cell count (SCC) (which is indicative of an immune response to infection). Intramammary infections (IMI) in sheep have a major economic impact reduced milk production, premature culling and even death of ewes. Over 130 species of bacteria have been associated with IMI in cattle and there is no reason to consider that a similar number of species cannot infect the sheep mammary gland (MG). Given the inevitability of IMI, this study hypothesizes that the sheep MG could host a microbiome with certain members affecting SCC.

The Project

Previous studies have been cross-sectional i.e. at one time point, with only one sample per subject and none have been conducted in sheep. This limits understanding causality; that is, how infection develops and what triggers development of disease. This study was therefore longitudinal, monitoring 30 sheep, each with two mammary gland halves, collecting milk samples over 8 weeks, providing 379 milk samples and data on sheep 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 banding patterns were analysed in a model to identify associations between individual bacterial species 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 DNA sequencing was developed. The DGGE and sequencing results show a persistent community has been detected over time, with similarities and differences by mammary gland half, lactation and age in sheep with no clinical signs of disease. Associations between individual bacterial species and SCC were identified through modelling. This study highlights the importance of further research to improve the understanding of what changes in a bacterial community lead to disease to advise farmers of management strategies to minimise IMIs. Analysis of all 379 samples by DNA sequencing and modelling will be used to directly test the study hypotheses in future work.

Student

Emma O'Monaghan