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Comparative Study
. 2012 Apr;50(4):1313-25.
doi: 10.1128/JCM.05971-11. Epub 2012 Feb 8.

Comparison of the Microflex LT and Vitek MS systems for routine identification of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry

Affiliations
Comparative Study

Comparison of the Microflex LT and Vitek MS systems for routine identification of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry

Delphine Martiny et al. J Clin Microbiol. 2012 Apr.

Abstract

This study compared the performance of three matrix-assisted laser desorption ionization-time of flight mass spectrometry systems: Microflex LT (Bruker Daltonics, Bremen, Germany), Vitek MS RUO (Axima Assurance-Saramis database; bioMérieux, Marcy l'Etoile, France), and Vitek MS IVD (bioMérieux). A total of 1,129 isolates, including 1,003 routine isolates, 73 anaerobes, and 53 bacterial enteropathogens, were tested on the Microflex LT and Axima Assurance devices. The spectra were analyzed using three databases: Biotyper (Bruker Daltonics), Saramis, and Vitek MS (bioMérieux). Among the routine isolates requiring identification to the species level (n = 986), 92.7% and 93.2% were correctly identified by the Biotyper and Vitek MS databases, respectively. The Vitek MS database is more specific for the identification of Streptococcus viridans. For the anaerobes, the Biotyper database often identified Fusobacterium isolates to only the genus level, which is of low clinical significance, whereas 20% of the Bacteroides species were not identified or were misidentified by the Vitek MS database. For the enteropathogens, the poor discrimination between Escherichia coli and Shigella explains the high proportion of unidentified organisms. In contrast to the Biotyper database, the Vitek MS database properly discriminated all of the Salmonella entrica serovar Typhi isolates (n = 5). The performance of the Saramis database was globally poorer. In conclusion, for routine procedures, the Microflex LT and Vitek-MS systems are equally good choices in terms of analytical efficiency. Other factors, including price, work flow, and lab activity, will affect the choice of a system.

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Figures

Fig 1
Fig 1
Distribution of the origins of the 1,003 routine isolates tested in this study. RTI, respiratory tract infections; SSI, skin and soft tissue infections; LIQ, normally sterile body fluids; UTI, urinary tract infections; EPID, epidemiological samples (methicillin-resistant S. aureus and extended-spectrum β-lactamase screening); GEN, genital tract infections; BC, blood cultures.
Fig 2
Fig 2
Influence of the growth medium on the percentage of correct species identifications for the two most frequently isolated species. CAP, colistin aztreonam blood agar plate; CLED, cystine lactose electrolyte-deficient agar; COL, Columbia agar; ESBL, chromogenic screening plate for the detection of extended-spectrum β-lactamase-producing organisms; MAC, MacConkey agar; MAN, mannitol agar; MRSA, chromogenic screening plate for detection of methicillin-resistant S. aureus.

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