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Use of Andromas and Bruker MALDI-TOF MS in the identification of Neisseria.

Florence MorelHervé JacquierMarine DesrochesVincent FihmanSylvain KumanskiEmmanuelle CambauJean-Winoc DecousserBéatrice Berçot
Published in: European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology (2018)
Through the past decade, MALDI-TOF MS has been recognized as a fast and robust tool for identification of most bacteria in clinical microbiology. However, the accuracy of this method to identify Neisseria species is still debated, and few data are available about commensal Neisseria species identification. In this study, we assessed two MALDI-TOF MS systems (Bruker Biotyper and Andromas) for the identification of 88, 18, and 29 isolates of Neisseria gonorrhoeae, Neisseria meningitidis, and commensal Neisseria species, respectively. All 88 isolates of N. gonorrhoeae were correctly identified using both systems, and most N. meningitidis and commensal Neisseria species were well identified: only 1/18 isolates of N. meningitidis was misidentified using Bruker Biotyper, and 1 isolate of Neisseria polysaccharea was misidentified as N. meningitidis using both systems. These results strengthen the possibility to use MALDI-TOF MS as a single method for Neisseria identification in routine, with excellent performance for N. gonorrhoeae identification. However, results should be interpreted prudently for N. meningitdis and commensal Neisseria species when isolated from genital and oropharyngeal samples where these both species can coexist.
Keyphrases
  • genetic diversity
  • mass spectrometry
  • bioinformatics analysis
  • machine learning
  • deep learning
  • electronic health record