Identification of airborne bacteria by 16S rDNA sequencing, MALDI-TOF MS and the MIDI microbial identification system

Author
Fykse, Else-Marie
Tjärnhage, Torbjörn
Humppi, Tarmo
Eggen, Vilde Sørvik
Ingebretsen, André
Skogan, Gunnar
Olofsson, Göran
Wästerby, Pär
Gradmark, Per-Åke
Larsson, Anders
Dybwad, Marius
Blatny, Janet Martha
Date Issued
2015
Keywords
Bakterier
Helsevurdering
Helse
Identifisering
Permalink
http://publications.ffi.no/handle/123456789/496
DOI
10.1007/s10453-015-9363-9
Collection
Articles
Description
Fykse, Else-Marie; Tjärnhage, Torbjörn; Humppi, Tarmo; Eggen, Vilde Sørvik; Ingebretsen, André; Skogan, Gunnar; Olofsson, Göran; Wästerby, Pär; Gradmark, Per-Åke; Larsson, Anders; Dybwad, Marius; Blatny, Janet Martha. Identification of airborne bacteria by 16S rDNA sequencing, MALDI-TOF MS and the MIDI microbial identification system. Aerobiologia 2015 ;Volum 31.(3) s. 271-281
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Abstract
The aim of this study was to collect and identify airborne bacteria in Norway, Sweden and Finland and to compare three different technologies for identifying collected airborne bacterial isolates: the “gold standard” method 16S rDNA sequencing, MALDI-TOF MS using the MALDI Biotyper 2.0 and the MIDI Sherlock® Microbial Identification System (MIDI MIS system). Airborne bacteria were collected during three different periods from May to October 2009 using air sampling directly on agar plates. A total of 140 isolates were collected during three sampling campaigns, and 74 % (103) of these isolates were analyzed by all three methods. The dominant genera in Norway and Finland were the gram-positive bacteria Bacillus and Staphylococcus, whereas the gram-negative bacterium Acinetobacter was the dominant genus in Sweden. Using 16S rDNA sequencing, MALDI-TOF MS and MIDI MIS analysis, 83, 79 and 75 %, respectively, of the isolates were identified and assigned to order or higher taxonomic levels. In this study, the MALDI-TOF MS combining with the MALDI Biotyper 2.0 classification tool was demonstrated to be a fast and reliable alternative for identifying the airborne bacterial isolates. These studies have increased knowledge about the airborne bacterial background in outdoor air, which can be useful for evaluating and improving the operational performance of biological detectors in various environments. To our knowledge, this is the first time that 16S rDNA sequencing, MALDI-TOF MS and MIDI MIS analysis technologies have been compared for their efficiency in identifying airborne bacteria.
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