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Staphylococcus aureusproduces capsular polysaccharides (CPs) both in vivo and under defined culture conditions being serotypes 5 and 8 the most prevalent. S. aureusisolates that fail to produce CP5 or CP8 are defined as non-typeable (NT). Loss of capsule expression, however, may lead to S. aureuspersistence in a chronically infected host. The prevalence of NT strains of S. aureusisolated from bovine mastitis varies according to the geographic origin of the strain. The aims of this work were to detect phenotypically and genotypically the capsular profile of 144 S. aureusisolated from bovine mastitis in Argentina, Chile, and Uruguay and explore the factors that are considered to be associated with capsule expression as presence of IS257, IScap, and agrtyping of non-related collection. The detection of the IS257, IScap, capgenes, and agrtyping was performed using PCR. The detection and quantification of capsular polysaccharide production were performed by ELISA assays. We found that 96% of the S. aureusisolates investigated carried cap5(8)genes but over 75% of strains do not express capsule in the three countries studied. However, only 6 isolates from Argentina carried the IScapelement that totally suppressed the expression of the capsule, suggesting that other factors could influence on CP expression. Moreover, the agrI/NT association was statistically significant suggesting that this profile is a phenomenon observed not only in other parts of the world but also in our region.

This work deals with the use of predictors to identify useful B-cell linear epitopes to develop immunoassays. Experimental techniques to meet this goal are quite expensive and time consuming. Therefore, we tested 5 free, online prediction methods (AAPPred, ABCpred, BcePred, BepiPred and Antigenic) widely used for predicting linear epitopes, using the primary structure of the protein as the only input. We chose a set of 65 experimentally well documented epitopes obtained by the most reliable experimental techniques as our true positive set. To compare the quality of the predictor methods we used their positive predictive value (PPV), i.e. the proportion of the predicted epitopes that are true, experimentally confirmed epitopes, in relation to all the epitopes predicted. We conclude that AAPPred and ABCpred yield the best results as compared with the other programs and with a random prediction procedure. Our results also indicate that considering the consensual epitopes predicted by several programs does not improve the PPV.