Performance of mass spectrometric identification of clinical Prevotella species using the VITEK MS system: A prospective multi-center study. (December 2018) - Ulger Toprak, Nurver; Alida C.M, Veloo; Urban, Edit; Wybo, Ingrid; Justesen, Ulrik S.; Jean-Pierre, Helene; Morris, Trefor; Akgul, Oncu; Kulekci, Guven; Soyletir, Guner; Nagy, Elisabeth; ,
Abstract: Prevotella species, members of the human microbiota, can cause opportunistic infections. Rapid and accurate identification of Prevotella isolates plays a critical role in successful treatment, especially since the antibiotic susceptibility profile differs between species. Studies, mostly carried out using the Matrix Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) Biotyper system, showed that MALDI-TOF MS is an accurate, rapid and satisfactory method for the identification of clinically important anaerobes. In this multi-center study, we assessed the performance of the MALDI-TOF MS VITEK MS system for the identification of clinical Prevotella isolates. A total of 508 Prevotella isolates, representing 19 different species, collected from 11 European countries, Kuwait and Turkey between January 2014 and April 2016, were identified using VITEK MS (v3.0). The reliability of the identification was assessed by 16S rRNA gene sequencing. Using VITEK MS, 422 (83.1%) of the 508 isolates were identified on the species level, 459 (90.4%) on the genus level. A total of 49 (9.6%) isolates were not identified correctly. 16S rRNA gene sequencing results showed that this was partly due to the fact that several species were not represented in the database. However, some species that were represented in the database were also not identified. Five Prevotella strains were misidentified at the genus level, 2 of these strains belonged to a species not represented in the database. In general, the VITEK MS offers a reliable and rapid identification of Prevotella species, however the databases needs to be expanded. Highlights: A total of 508 clinical isolates from 13 countries were studied. 19 different Prevotella species were identified by using VITEK MS (v3.0). The species and genus level identification were compared to 16S rRNA gene sequencing. 83% of the isolates were identified at the species level, 90.4% at the genus level.