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This study compared the accuracy of a new MALDI-TOF mass spectrometry system, ASTA MicroIDSys system, with that of MALDI Biotyper system for the identification of reference and clinical bacterial and yeast strains. The identification accuracy of the 2 systems was compared using a total of 406 strains comprising 142 aerobic and 180 anaerobic bacterial strains and 84 yeast strains. The genus and species identification rates were 98.0% and 89.4% using MicroIDSys and 96.1% and 89.4% using Biotyper, respectively. The species identification rates of MicroIDSys and Biotyper for aerobic bacteria were 93.0% and 97.2%, respectively, and those for anaerobic bacteria were 85.6% and 81.7%, respectively. The accuracy of yeast identification at the species level was 91.7% using MicroIDSys and 92.9% using Biotyper. These findings indicate that MicroIDSys could be useful for the accurate identification of bacteria and yeast in clinical microbiology laboratories.

We evaluated the ability of the Filamentous Fungi Library 1.0 of the MALDI-TOF MS Biotyper system to identify 345 clinical Aspergillus isolates from 11 Korean hospitals. Compared with results of the internal transcribed spacer region sequencing, the frequencies of correct identification at the species-complex level were 94.5% and 98.8% with cutoff values of 2.0 and 1.7, respectively. Compared with results of β-tubulin gene sequencing, the frequencies of correct identification at the species level were 96.0% (cutoff 2.0) and 100% (cutoff 1.7) for 303 Aspergillus isolates of five common, non-cryptic species, but only 4.8% (cutoff 1.7) and 0% (cutoff 2.0) for 42 Aspergillus isolates of six cryptic species (identifiable by β-tubulin or calmodulin sequencing). These results show that the MALDI Biotyper using the Filamentous Fungi Library version 1.0 enables reliable identification of the majority of common clinical Aspergillus isolates, although the database should be expanded to facilitate identification of cryptic species.

To compare the identification accuracies of VITEK 2 (bioMérieux), MicroScan (Siemens Healthcare), and Phoenix (Becton Dickinson), microbial identification was performed on 160 clinical isolates and 50 reference strains on each of these 3 systems, using the appropriate identification kit provided by each system. Of the 142 clinical isolates that were identified at the species level, VITEK 2, MicroScan, and Phoenix correctly identified 93.7%, 82.4%, and 93.0%, and incorrectly identified 2.1%, 7.0%, and 0%, respectively. In the reference strain tests, VITEK 2, MicroScan, and Phoenix correctly identified 55.3%, 54.4%, and 78.0% of the reference strains at the species level and incorrectly identified 10.6%, 13.0%, and 6.0% of the reference strains, respectively. In conclusion, the identification rate of VITEK 2, Phoenix, and MicroScan was high or acceptable on clinical isolates. Phoenix showed a significantly higher performance than VITEK 2 or MicroScan in identifying the reference strains.

Since accurate identification of species is necessary for proper treatment of Acinetobacter infections, we compared the performances of 4 bacterial identification methods using 167 Acinetobacter clinical isolates to identify the best identification method. To secure more non-baumannii Acinetobacter (NBA) strains as target strains, we first identified Acinetobacter baumannii in a total of 495 Acinetobacter clinical isolates identified using the VITEK 2 system. Because 371 of 495 strains were identified as A. baumannii using gyrB multiplex 1 PCR and blaOXA51-like PCR, we performed rpoB gene sequencing and 16S rRNA gene sequencing on remaining 124 strains belonging to NBA and 52 strains of A. baumannii. For identification of Acinetobacter at the species level, the accuracy rates of rpoB gene sequencing, 16S rRNA gene sequencing, gyrB multiplex PCR, and the VITEK 2 were 98.2%, 93.4%, 77.2%, and 35.9%, respectively. The gyrB multiplex PCR seems to be very useful for the detection of ACB complex because its concordance rates to the final identification of strains of ACB complex were 100%. Both the rpoB gene sequencing and the 16S rRNA gene sequencing may be useful in identifying Acinetobacter.