The recombination dynamics of Staphylococcus aureus inferred from spA gene

Célio D. Santos-Júnior, António Veríssimo, Joana Costa

Given the role of spA as a pivotal virulence factor decisive for Staphylococcus aureus ability to escape from innate and adaptive immune responses, one can consider it as an object subject to adaptive evolution and that variations in spA may uncover pathogenicity variations. The population genetic structure was deduced from the extracellular domains of SpA gene sequence (domains A-E and the X-region) and compared to the MLST-analysis of 41 genetically diverse methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) S. aureus strains. Incongruence between tree topologies was noticeable and in the inferred spA tree most MSSA isolates were clustered in a distinct group. Conversely, the distribution of strains according to their spA-type was not always congruent with the tree inferred from the complete spA gene foreseeing that spA is a mosaic gene composed of different segments exhibiting different evolutionary histories. Evidences of a network-like organization were identified through several conflicting phylogenetic signals and indeed several intragenic recombination events (within subdomains of the gene) were detected within and between CC's of MRSA strains. The alignment of SpA sequences enabled the clustering of several isoforms as a result of non-randomly distributed amino acid variations, located in two clusters of polymorphic sites in domains D to B and Xr (a). Nevertheless, evidences of cluster specific structural arrangements were detected reflecting alterations on specific residues with potential impact on S. aureus pathogenicity. The detection of positive selection operating on spA combined with frequent non-synonymous mutations, domain duplication and frequent intragenic recombination events represent important mechanisms acting in the evolutionary adaptive mechanism promoting spA genetic plasticity. These findings argue that crucial allelic forms correlated with pathogenicity can be identified by sequences analysis enabling the design of more robust schemes.