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A comprehensive dissection of pneumococcal-host interactions (PNEUMOPATH)
Start date: Mar 1, 2009, End date: Aug 31, 2012 PROJECT  FINISHED 

"This project is a fundamental, comprehensive study of the host-pathogen interactions during infection with Streptococcus pneumoniae. The expectation is that the basic knowledge gained from this work will give new targets for vaccination, diagnosis and treatment. In PNEUMOPATH, academic and industrial partners will work together in six scientific workpackages. 1) The molecular epidemiology of antibiotic resistant pneumococci 2) The genetic basis of disease susceptibility in the human host and in mice 3) Molecular aspects of virulence and host response in animal models of pneumococcal carriage and disease 4) Molecular aspects of virulence and host response in human cell culture systems 5) Pneumococcal cell biology to determine the role of central metabolic processes and the link to virulence 6) Integrated bioinformatics and data management It is accepted that the outcome of pneumococcal infection is determined by the interplay of both host and pathogen attributes. Pneumococcal isolates vary in the repertoire of genes that they possess. Hence the contribution of an individual factor to the infectious process may vary according to the other host and pathogen factors that are present. To date, study of infection has tended to be a reductionist approach, considering the contribution of each virulence factor or host factor in isolation. Consequently, in searching for targets for antimicrobial therapy or for enhancement of host defence, the contribution of individual factors may be inaccurately estimated. This project will be radically different. Rather than using targeted mutagenesis to create strains of different phenotype for testing, PNEUMOPATH will be a systems biology approach with a checkerboard experimental design Panels of resistant/non-resistant carriage and disease pneumococcal isolates will be used to challenge in vivo and in vitro models, followed by integrated management and analysis of the data with a new semantic web bioinformatic infrastructure."
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