Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/105105
Title: MALDI-TOF/MS identification of species from the Acinetobacter baumannii (Ab) group revisited: inclusion of the novel A. seifertii and A. dijkshoorniae species
Author: Marí Almirall, Marta
Cosgaya, Clara
Higgins, Paul G.
Assche, Ado Van
Telli, Murat
Huys, Geert
Lievens, Bart
Seifert, Harald
Dijkshoorn, Lenie
Roca, Ignasi
Vila Estapé, Jordi
Keywords: Bacteris gramnegatius
Resistència als medicaments
Gram-negative bacteria
Drug resistance
Issue Date: 2-Dec-2016
Publisher: Elsevier
Abstract: OBJECTIVES: Rapid identification of Acinetobacter species is critical since 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 have also 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. METHODS: Species characterisation was performed by rpoB-clustering and MLSA. MALDI-TOF/MS spectra were recovered from formic acid/acetonitrile bacterial extracts overlaid with alpha-cyano-4-hydroxy-cinnamic acid matrix on a MicroflexLT in linear positive mode and 2,000-20,000 m/z range mass. Spectra were examined with the ClinProTools v2.2 software. Mean spectra (MSP) were created with the BioTyper software. 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 3 A. seifertii, 2 A. dijkshoorniae and 2 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. 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.
Note: Versió postprint del document publicat a: http://dx.doi.org/10.1016/j.cmi.2016.11.020
It is part of: Clinical Microbiology and Infection, 2016
Related resource: http://dx.doi.org/10.1016/j.cmi.2016.11.020
URI: http://hdl.handle.net/2445/105105
ISSN: 1198-743X
Appears in Collections:Articles publicats en revistes (ISGlobal)

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