The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae , the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for ≈80% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.

Neisseria meningitidis is a major cause of bacterial septicemia and meningitis. Sequence variation of surface-exposed proteins and cross-reactivity of the serogroup B capsular polysaccharide with human tissues have hampered efforts to develop a successful vaccine. To overcome these obstacles, the entire genome sequence of a virulent serogroup B strain (MC58) was used to identify vaccine candidates. A total of 350 candidate antigens were expressed in Escherichia coli, purified, and used to immunize mice. The sera allowed the identification of proteins that are surface exposed, that are conserved in sequence across a range of strains, and that induce a bactericidal antibody response, a property known to correlate with vaccine efficacy in humans.

We describe a proteomic approach for identifying bacterial surface-exposed proteins quickly and reliably for their use as vaccine candidates. Whole cells are treated with proteases to selectively digest protruding proteins that are subsequently identified by mass spectrometry analysis of the released peptides. When applied to the sequenced M1_SF370 group A Streptococcus strain, 68 PSORT-predicted surface-associated proteins were identified, including most of the protective antigens described in the literature. The number of surface-exposed proteins varied from strain to strain, most likely as a consequence of different capsule content. The surface-exposed proteins of the highly virulent M23_DSM2071 strain included 17 proteins, 15 in common with M1_SF370. When 14 of the 17 proteins were expressed in E. coli and tested in the mouse for their capacity to confer protection against a lethal dose of M23_DSM2071, one new protective antigen (Spy0416) was identified. This strategy overcomes the difficulties so far encountered in surface protein characterization and has great potential in vaccine discovery.

olate dispersal behavior to the landscape level (17, 21,27,28). Explicit tests of such models are needed (18). The tight fit between observed and predicted patterns of seed rain in our habitat patches provides strong support for the key assumption that small-scale behavioral responses can drive landscape-scale distributional patterns. From a conservation perspective, impacts of corridors can be predicted on the basis of behaviors that are relatively simple to measure (29).