Citation

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Immunization with Staphylococcus aureus Clumping Factor B, a Major Determinant in Nasal Carriage, Reduces Nasal Colonization in a Murine Model

Schaffer AC1, Solinga RM, Cocchiaro J, Portoles M, Kiser KB, Risley A, Randall SM, Valtulina V, Speziale P, Walsh E, Foster T, Lee JC

Staphylococcus aureus is responsible for a wide range of infections, including soft tissue infections and potentially fatal bacteremias. The primary niche for S. aureus in humans is the nares, and nasal carriage is a documented risk factor for staphylococcal infection. Previous studies with rodent models of nasal colonization have implicated capsule and teichoic acid as staphylococcal surface factors that promote colonization. In this study, a mouse model of nasal colonization was utilized to demonstrate that S. aureus mutants that lack clumping factor A, collagen binding protein, fibronectin binding proteins A and B, polysaccharide intercellular adhesin, or the accessory gene regulator colonized as well as wild-type strains colonized. In contrast, mutants deficient in sortase A or clumping factor B (ClfB) showed reduced nasal colonization. Mice immunized intranasally with killed S. aureus cells showed reduced nasal colonization compared with control animals. Likewise, mice that were immunized systemically or intranasally with a recombinant vaccine composed of domain A of ClfB exhibited lower levels of colonization than control animals exhibited. A ClfB monoclonal antibody (MAb) inhibited S. aureus binding to mouse cytokeratin 10. Passive immunization of mice with this MAb resulted in reduced nasal colonization compared with the colonization observed after immunization with an isotype-matched control antibody. The mouse immunization studies demonstrate that ClfB is an attractive component for inclusion in a vaccine to reduce S. aureus nasal colonization in humans, which in turn may diminish the risk of staphylococcal infection. As targets for vaccine development and antimicrobial intervention are assessed, rodent nasal colonization models may be invaluable.