A MALDI-TOF MS database with broad genus coverage for species-level identification of Brucella.

• Published in: PLOS Neglected Tropical Diseases
• Main Authors: Jennifer Mesureur, Sandrine Arend, Béatrice Cellière, Priscillia Courault, Pierre-Jean Cotte-Pattat, Heather Totty, Parampal Deol, Virginie Mick, Victoria Girard, Joanne Touchberry, Vanessa Burrowes, Jean-Philippe Lavigne, David O'Callaghan, Valérie Monnin, Anne Keriel
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science (PLoS) 2018
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Public aspects of medicine; RA1-1270; Arctic
• Online Access: https://doi.org/10.1371/journal.pntd.0006874; https://doaj.org/article/50ff8634f1134ec2913508232483a142

Brucella are highly infectious bacterial pathogens responsible for a severely debilitating zoonosis called brucellosis. Half of the human population worldwide is considered to live at risk of exposure, mostly in the poorest rural areas of the world. Prompt diagnosis of brucellosis is essential to prevent complications and to control epidemiology outbreaks, but identification of Brucella isolates may be hampered by the lack of rapid and cost-effective methods. Nowadays, many clinical microbiology laboratories use Matrix-Assisted Laser Desorption Ionization-Time Of Flight mass spectrometry (MALDI-TOF MS) for routine identification. However, lack of reference spectra in the currently commercialized databases does not allow the identification of Brucella isolates. In this work, we constructed a Brucella MALDI-TOF MS reference database using VITEK MS. We generated 590 spectra from 84 different strains (including rare or atypical isolates) to cover this bacterial genus. We then applied a novel biomathematical approach to discriminate different species. This allowed accurate identification of Brucella isolates at the genus level with no misidentifications, in particular as the closely related and less pathogenic Ochrobactrum genus. The main zoonotic species (B. melitensis, B. abortus and B. suis) could also be identified at the species level with an accuracy of 100%, 92.9% and 100%, respectively. This MALDI-TOF reference database will be the first Brucella database validated for diagnostic and accessible to all VITEK MS users in routine. This will improve the diagnosis and control of brucellosis by allowing a rapid identification of these pathogens.