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MALDI-TOF/MS identification of species from the Acinetobacter baumannii (Ab) group revisited: inclusion of the novel A. seifertii and A. dijkshoorniae species.

Authors :
Marí-Almirall M
Cosgaya C
Higgins PG
Van Assche A
Telli M
Huys G
Lievens B
Seifert H
Dijkshoorn L
Roca I
Vila J
Source :
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases [Clin Microbiol Infect] 2017 Mar; Vol. 23 (3), pp. 210.e1-210.e9. Date of Electronic Publication: 2016 Dec 03.
Publication Year :
2017

Abstract

Objectives: Rapid identification of Acinetobacter species is critical as members of the A. baumannii (Ab) group differ in antibiotic susceptibility and clinical outcomes. A. baumannii, A. pittii, and A. nosocomialis can be identified by MALDI-TOF/MS, while the novel species A. seifertii and A. dijkshoorniae cannot. Low identification rates for A. nosocomialis also have been reported. We evaluated the use of MALDI-TOF/MS to identify isolates of A. seifertii and A. dijkshoorniae and revisited the identification of A. nosocomialis to update the Bruker taxonomy database.<br />Methods: Species characterization was performed by rpoB-clustering and MLSA. MALDI-TOF/MS spectra were recovered from formic acid/acetonitrile bacterial extracts overlaid with α-cyano-4-hydroxy-cinnamic acid matrix on a MicroflexLT in linear positive mode and 2000-20 000 m/z range mass. Spectra were examined with the ClinProTools v2.2 software. Mean spectra (MSP) were created with the BioTyper software.<br />Results: Seventy-eight Acinetobacter isolates representative of the Ab group were used to calculate the average spectra/species and generate pattern recognition models. Species-specific peaks were identified for all species, and MSPs derived from three A. seifertii, two A. dijkshoorniae, and two A. nosocomialis strains were added to the Bruker taxonomy database, allowing successful identification of all isolates using spectra from either bacterial extracts or direct colonies, resulting in a positive predictive value (PPV) of 99.6% (777/780) and 96.8% (302/312), respectively.<br />Conclusions: The use of post-processing data software identified statistically significant species-specific peaks to generate reference signatures for rapid accurate identification of species within the Ab group, providing relevant information for the clinical management of Acinetobacter infections.<br /> (Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1469-0691
Volume :
23
Issue :
3
Database :
MEDLINE
Journal :
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Publication Type :
Academic Journal
Accession number :
27919649
Full Text :
https://doi.org/10.1016/j.cmi.2016.11.020