Comparison of Phenotypic and Genotypic Techniques for Identification of Unusual Aerobic Pathogenic Gram-Negative Bacilli

Abstract

Rapid and accurate identification of bacterial pathogens is a fundamental goal of clinical microbiology, but one that is difficult or impossible for many slow-growing and fastidious organisms. We used identification systems based on cellular fatty acid profiles (Sherlock; MIDI, Inc., Newark, Del.), carbon source utilization (Microlog; Biolog, Inc., Hayward, Calif.), and 16S rRNA gene sequence (MicroSeq; Perkin-Elmer Applied Biosystems Division, Foster City, Calif.) to evaluate 72 unusual aerobic gram-negative bacilli isolated from clinical specimens at the Mayo Clinic. Compared to lengthy conventional methods, Sherlock, Microlog, and MicroSeq were able to identify 56 of 72 (77.8%), 63 of 72 (87.5%), and 70 of 72 (97.2%) isolates to the genus level ( P = 0.002) and 44 to 65 (67.7%), 55 of 65 (84.6%), and 58 of 65 (89.2%) isolates to the species level ( P = 0.005), respectively. Four Acinetobacter and three Bordetella isolates which could not be identified to the species level by conventional methods were identified by MicroSeq. In comparison to the full 16S rDNA sequences, the first 527 bp provided identical genus information for all 72 isolates and identical species information for 67 (93.1%) isolates. These data show that MicroSeq provides rapid, unambiguous identification of clinical bacterial isolates. The improved turnaround time provided by genotypic identification systems may translate into improved clinical outcomes.