RESUMO
The Vitek MS v2.0 matrix-assisted laser desorption ionization-time of flight mass spectrometry system accurately distinguished Streptococcus pneumoniae from nonpneumococcal S. mitis group species. Only 1 of 116 nonpneumococcal isolates (<1%) was misidentified as S. pneumoniae. None of 95 pneumococcal isolates was misidentified. This method provides a rapid, simple means of discriminating among these challenging organisms.
Assuntos
Erros de Diagnóstico/estatística & dados numéricos , Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz/métodos , Infecções Estreptocócicas/microbiologia , Streptococcus mitis/classificação , Streptococcus mitis/isolamento & purificação , Streptococcus pneumoniae/classificação , Streptococcus pneumoniae/isolamento & purificação , Humanos , Infecções Estreptocócicas/diagnóstico , Streptococcus mitis/química , Streptococcus pneumoniae/químicaRESUMO
The optimal management of fungal infections is correlated with timely organism identification. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) is revolutionizing the identification of yeasts isolated from clinical specimens. We present a multicenter study assessing the performance of the Vitek MS system (bioMérieux) in identifying medically important yeasts. A collection of 852 isolates was tested, including 20 Candida species (626 isolates, including 58 C. albicans, 62 C. glabrata, and 53 C. krusei isolates), 35 Cryptococcus neoformans isolates, and 191 other clinically relevant yeast isolates; in total, 31 different species were evaluated. Isolates were directly applied to a target plate, followed by a formic acid overlay. Mass spectra were acquired using the Vitek MS system and were analyzed using the Vitek MS v2.0 database. The gold standard for identification was sequence analysis of the D2 region of the 26S rRNA gene. In total, 823 isolates (96.6%) were identified to the genus level and 819 isolates (96.1%) were identified to the species level. Twenty-four isolates (2.8%) were not identified, and five isolates (0.6%) were misidentified. Misidentified isolates included one isolate of C. albicans (n = 58) identified as Candida dubliniensis, one isolate of Candida parapsilosis (n = 73) identified as Candida pelliculosa, and three isolates of Geotrichum klebahnii (n = 6) identified as Geotrichum candidum. The identification of clinically relevant yeasts using MS is superior to the phenotypic identification systems currently employed in clinical microbiology laboratories.
