Abstract
The identification of an appropriate animal model for use in the development of meningococcal vaccines has been a challenge as humans are the only natural host for Neisseria meningitidis. Small animal models have been developed and are widely used to study the efficacy or immunogenicity of vaccine formulations generated against various diseases. Here, we describe the development and optimization of a mouse model for assessing the immunogenicity of candidate tetravalent meningococcal polysaccharide (MenACYW-TT) protein conjugate vaccines. Three inbred (BALB/c [H-2d], C3H/HeN [H-2k], or C57BL/6 [H-2b]) and one outbred (ICR [H-2g7]) mouse strains were assessed using serial two-fold dose dilutions (from 2 µg to 0.03125 µg per dose of polysaccharide for each serogroup) of candidate meningococcal conjugate vaccines. Groups of 10 mice received two doses of the candidate vaccine 14 days apart with serum samples obtained 14 days after the last dose for the evaluation of serogroup-specific anti-polysaccharide IgG by ELISA and bactericidal antibody by serum bactericidal assay (SBA). C3H/HeN and ICR mice had a more dose-dependent antibody response to all four serogroups than BALB/c and C57Bl/6 mice. In general, ICR mice had the greatest antibody dose-response range (both anti-polysaccharide IgG and bactericidal antibodies) to all four serogroups and were chosen as the model of choice. The 0.25 µg per serogroup dose was chosen as optimal since this was in the dynamic range of the serogroup-specific dose-response curves in most of the mouse strains evaluated. We demonstrate that the optimized mouse immunogenicity model is sufficiently sensitive to differentiate between conjugated polysaccharides, against unconjugated free polysaccharides and, to degradation of the vaccine formulations. Following optimization, this optimized mouse immunogenicity model has been used to assess the impact of different conjugation chemistries on immunogenicity, and to screen and stratify various candidate meningococcal conjugate vaccines to identify those with the most desirable profile to progress to clinical trials.