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    On the track of β-lactam resistance: Studies on the regulation of methicillinresistance in Staphylococcus aureus

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    Dissertação para obtenção do Grau de Doutor em BiologiaMethicillin-resistant Staphylococcus aureus (MRSA) is an important human pathogen, causing a wide range of infections. MRSA has not only developed an intrinsic resistance to all β-lactams, but has also acquired resistance to virtually all classes of antimicrobial agents. The characteristic MRSA phenotype is conferred by the presence of mecA gene which is regulated by a sensor-inducer (MecR1) and a repressor (MecI). However, mecA induction by its cognate sensor/inducer is very inefficient and, therefore, it is believed that optimal expression of β-lactam resistance in MRSA requires a non-functional MecR1-MecI system. Surprisingly, no correlation was found between the presence of functional MecR1- MecI and the level of β-lactam resistance in a representative collection of epidemic MRSA strains, suggesting the existence of other mecA regulators. In these studies, we show that the mecA regulatory locus is not a two-component system but, actually, it is a three-component system containing besides mecR1-mecI, the previously unidentified antirepressor mecR2. The crystal structure of MecR2 reveals a three-domain architecture, with an N-terminal DNA-binding-like domain, an intermediate scaffold domain, and a C-terminal dimerization domain, important to the functional dimeric oligomerization state. MecR2 disturbs the binding of the repressor MecI to the mecA promoter, which leads to its proteolytic inactivation independently from MecR1, presumably by non-specific cytoplasmatic proteases. Our data also demonstrates that in the presence of functional mecR1-mecI genes, mecR2 is essential for a robust induction of mecA transcription and, consequently, for the optimal expression of resistance phenotype in MRSA. These observations point to a revision of the current model for the transcriptional control of the mecA gene.Fundação para a Ciência e a Tecnologia - Doctoral Project (SFRH/BD/38316/2007
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