Prediction of phenotype from genotype with respect to bacterial infection

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The DNA sequence of a bacterial genome (genotype) encodes all the traits (phenotypes) displayed by an individual organism. DNA sequences can now be read quickly and cost effectively, providing new opportunities to exploit this information in the control of bacterial diseases.This project will produce the information required to successfully predict the ability of a bacterium to cause disease (virulence) directly from its genome. To achieve this, it will be necessary to identify the bacterial components required for virulence, their variation and determine how such variation impacts the virulence phenotype.This investigation will focus on bovine mastitis, the most common infectious disease of dairy cattle (~1 million cases /year in the UK). Mastitis typically results from intramammary infection by one of a variety of different bacterial species; the most common in the UK being Streptococcus uberis (~30% of all cases) and this bacterium will be the subject of this study.Signs of mastitis result from spiralling inflammation due to the inability of the immune defences to clear the infection. The disease results in damage to milk producing tissue and under production of milk and production of milk that is unfit for human consumption. In the UK alone, mastitis results in lost milk production equivalent to ~1M tonnes. The endemic nature of the disease creates major inefficiencies within dairy production, leading to substantial economic impact and significant effects on animal welfare and the environmental sustainability of dairy farming. Control (prevention and treatment) of mastitis to its current level in the UK requires ~3 tonnes of antibiotic /year and new, more effective methods of prevention / treatment are required urgently.In this project, a combination of mutation and DNA sequencing technology will be used to identify genes in S. uberis that contribute to the initial stages of disease. Genetic lesions (mutations) introduced in to the bacterium (mutant) will be located on the genome by DNA sequencing. Analysis of 100,000 bacterial mutants, each carrying a different mutation, before and after colonisation of the mammary gland will permit identification of genes required for colonisation. The same technology will be used to identify genes required at specific stages of colonisation (growth in milk, resistance to immune defences) in laboratory models.Not all strains of S. uberis are equally virulent. Some readily cause mastitis, while others only transiently infect the mammary gland in low numbers. We will sequence the genome of 600 strains of S. uberis from diseased and non-diseased animals and quantify the ability of 500 of these to colonise the mammary gland, grow in milk and resist the mammary gland immune defences. These two data sets will be analysed in a variety ways. A detailed comparison of those genes previously identified as important for virulence will determine those individual and combinations of gene variants that align with virulence. Also, a computer based analysis will compare short lengths of each genome sequence to all other genome sequences to provide a profile of DNA sequences that defines more virulent from less virulent in a quantifiable manner.A combination of these analyses will be used to predict the virulence of 100 S. uberis strains directly from their genome sequence and these strains will be tested in the relevant model system to determine the accuracy of the prediction.Conducting this investigation will not only provide an example study of how genome sequences may be related to virulence in an effective and useful manner, but will also generate a robust platform of information that will underpin scientifically robust development of interventions to control a major infectious disease with substantial implications for animal welfare and environmentally sustainable food production