Identification of enterococcal strains using an inductive learning algorithm

Enterococci have recently emerged as an important cause of various serious infection. They are intrinsically resistant to various antimicrobial agents and effective therapy depends primarily on the penicillins, vancomycin and aminoglycosides. Enterococcus faecium isolates are significantly more likely to be resistant to the penicillins in contrast to Enterococcus faecalis isolates.2 Emergence of vancomycin resistant enterococci, especially E. faecium has become an increasing problem. Enterococci highly resistant to aminoglycosides are also found, frequently E. faecium isolates. Identification of enterococcal isolates to the species level is useful because it can help assess species specific antimicrobial resistance patterns.2 Species identification of enterococci has also been found to be of epidemiological importance. Several methods for the identification of microorganisms from this genus have been described.1, 3 New taxonomic changes and identification of new species impose a necessity for new identification schemes.