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Large-scale evaluation of bacterial genome content for the identification of epidemiological and virulence bases in MRSA

Defense Thèse de privat-docent : Univ. Genève, 2010
Abstract Staphylococcus aureus is a major human pathogen responsible for a wide diversity of infections ranging from localized to life threatening diseases. From 1961 and the emergence methicillin resistant S. aureus (MRSA), this bacterium has shown particular capacity to survive and adapt to drastic environmental changes and we observed since beginning of the nineties its worldwide spreading. Until recently, S. aureus was considered as the prototype of a nosocomial pathogen but it has now clearly shown also responsible for outbreaks in the community. Several recent reports suggest therefore that the epidemiology of MRSA is changing. The understanding of pathogenicity, virulence and emergence of epidemic clones within MRSA populations is not clearly defined, despite several attempts to identify common molecular features between strains that share similar epidemiological and/or virulence behavior. These studies included: i) pattern profiling of bacterial adhesins, ii) analysis of clonal complex groups, iii) molecular genotyping, or iv) enterotoxins content studies. To date, all approaches failed unraveling correlation between molecular determinants and clinical outcomes. We hypothesize that parameters contributing to strain virulence or to the capacity to evolve from a non-invasive to an invasive behavior are contained within the genetic material of the bacterium. The utilization of massively parallel methods of analysis is therefore ideal to study the contribution of this genetic make-up. Our evaluations are therefore performed on the entire genome including coding sequences (CDS) as well as non coding sequences. Ideally, these determinations should allow appreciating micro and macro evolution of MRSA and identifying specific genomic markers of evolution towards invasive or highly virulent phenotypes.
Keywords Staphylococcus aureusSmall RNAGenomeTranscriptomeSequencingExpressionSNPsMicroarrayRestriction systems
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