Multiple Techniques for Size Determination of Generalized Modules for Membrane Antigens from Salmonella typhimurium and Salmonella enteritidis .

In the last years, outer membrane vesicles have attracted a lot of attention for the development of vaccines against bacterial pathogens. Extracellular vesicles can be obtained in high yields by genetic mutations, resulting in generalized modules for membrane antigens (GMMA). Methods to check the quality, consistency of production, and stability of GMMA vaccines are of fundamental importance. In this context, analytical methods for size distribution determination and verifying the integrity and possible aggregation of GMMA particles are strongly needed. Herein, GMMA particle size distribution has been evaluated by means of three different techniques. Dynamic light scattering (DLS), multiangle light scattering (MALS) coupled with high-performance liquid chromatography-size exclusion chromatography (SEC), and nanoparticle tracking analysis (NTA) have been compared to characterize GMMA from different mutants of Salmonella typhimurium and Salmonella enteritidis strains. We found that the presence of O-antigen chains on GMMA determined higher Z -average diameters by DLS compared to size estimation by MALS and that the hydrodynamic diameter increased with the number of O-antigen chains per GMMA particle. In the case of SEC-MALS, the size of the whole population better reflects the size of the most abundant particles, whereas DLS diameter is more influenced by the presence of larger particles in the sample. SEC-MALS and NTA are preferable to DLS for the analysis of bimodal samples, as they better distinguish populations of different size. MALS coupled to a size exclusion chromatography module also allows checking the purity of GMMA preparations, allowing determination of generally occurring contaminants such as soluble proteins and DNA. NTA permits real-time visualization with simultaneous tracking and counting of individual particles, but it is deeply dependent on the choice of data analysis parameters. All of the three techniques have provided complementary information leading to a more complete characterization of GMMA particles.