A GRAPH-THEORY METHOD TO ESTABLISH SEROLOGICAL RELATIONSHIPS WITHIN ABACTERIAL TAXON, WITH EXAMPLE FROM PORPHYROMONAS-GINGIVALIS

This paper develops a rationale for transforming serological data obta ined by indirect immunofluorescence (IF) into a meaningful character-s tate matrix, and uses this matrix for numerical phylogenetic analysis. Typically, immunofluorescence data come in square asymmetrical matric es; columns correspond to strains used for adsorption and rows to stra ins used in the IF test. Such matrices can be decomposed into a symmet ric and a skew-symmetric part. We first show that all pertinent biolog ical information needed to reconstruct a phylogeny lies in the skew-sy mmetric component. Then we show how to transform the skew-symmetric ma trix into a character-state tree, and how to obtain a binary character -state matrix from it. The character-state matrices obtained for diffe rent hyperimmune serum antibodies are assembled into a total character -state matrix, on which phylogenetic analysis is conducted. The data t hat motivated this methodological development concern Porphyromonas gi ngivalis, a major pathogen in adult periodontitis. Various proposals h ave been put forward in the literature, concerning the number of major serogroups found in this taxon. Six human and two animal strains of P . gingivalis were subjected to serotyping and to the phylogenetic anal ysis described above. Using a test of statistical significance recentl y developed to compare independently-obtained phylogenetic trees, or t o compare hypotheses to trees, we show that our results best fit the h ypothesis that there are three groups of serotypes, one animal and two human. Alternate hypotheses are not, or less strongly supported by ou r data. The algorithms developed to implement the new phylogenetic ana lysis method are presented in appendices.