Simple and inexpensive but highly discriminating method for computer-assisted DNA fingerprinting of Pseudomonas aeruginosa

We describe here a method for computer-assisted fingerprinting of Pseudomon as aeruginosa. In this method, DNA is digested with San, and bands with mol ecular sizes of greater than or equal to9.7 kb are visually scored after el ectrophoresis on agarose gels. Pattern scores are entered into a Microsoft Excel database. In scoring, the number of bands within each of a set of mol ecular size ranges is scored, rather than the absolute molecular size of ea ch band, substantially enhancing the speed and reproducibility of the metho d, while eliminating the need for using expensive gel scanning equipment an d software. Pattern scores are used to generate matrices of genetic distanc e values, which can be visualized in neighbor-joining trees. The method rel iably distinguishes two epidemiologically unrelated isolates in 99.3% of al l comparisons, The genetic relationships between isolates observed with the method were consistent with those obtained by analysis of two P. aeruginos a genes, indicating that it provides valid estimates of genetic divergence between isolates. Using the method, respiratory tract isolates from cystic fibrosis patients in Green Lane Hospital in Auckland, New Zealand, were sho wn to be genetically less diverse than epidemiologically unrelated isolates from other patients, This finding was not due to the existence of clusters of related strains specialized toward colonization of the respiratory trac t and thus was indicative of transmission between patients. Analysis of mul tiple isolates from individual cystic fibrosis patients suggested that up t o five separate clusters of genetically related strains may simultaneously be present in a patient. The method described should significantly enhance our ability to investigate the epidemiology of P. aeruginosa.