Pathogenic bacteria exhibit a remarkable degree of genetic plasticity in order to adapt to a wide array of host environments. Mechanisms of this programmed process include phase variation by DNA repeats, gene polymorphism, site-specific DNA rearrangements, and differential methylation. This variation at the DNA level translates into phenotypic changes, most often in proteins involved in host-pathogen interactions, allowing the pathogen to evade host defenses and thrive under stressful conditions. Phase variation is a particularly attractive starting point for studying this inherent genetic instability because quite an extensive database has been compiled of its occurrence. Because phase variability is an inherently dynamic process that involves mutability of the DNA sequence itself, phase variation in N. gonorrhoeae will be studied through proteomics, a field whose aim is to capture the in vivo state of the cell. Specifically, the problem of linking mass spectrometry data directly to uninterpreted genome will be addressed by introducing a novel approach that combines peptide mass fingerprint and intact protein mass spectroscopy data with a simple gene finding approach. Once protein is linked to genome, a Hidden Markov Model (HMM) method will be developed to predict the nature of DNA repeat that produced a given phase variable protein. This work will provide the first computational model, ultimately generalizable across species, of an important determinant of virulence.
