Application of MALDI-TOF MS for the subtyping of Arcobacter butzleri strains and comparison with their MLST and PFGE types
Introduction
The genus Arcobacter is an unusual taxon within the epsilon subdivision of Proteobacteria containing both pathogenic and free-living species found in a wide range of environments (Miller et al., 2007). It has long been considered an emerging human enteric pathogen linked to gastrointestinal illnesses (Collado and Figueras, 2011; Hsu and Lee, 2015). Although several aspects of Arcobacter epidemiology and virulence are starting to be clarified, key reservoirs and mechanisms of transmission have yet to be fully determined (Collado and Figueras, 2011). Arcobacter species are ubiquitous in animals, in a variety of foods of animal and non-animal origin, and in both aquatic and food-processing environments (Collado and Figueras, 2011; Merga et al., 2013), usually showing a high genotype diversity in all these sources. Arcobacter butzleri is the best characterized of all Arcobacter species. It is probably an environmental organism (Miller et al., 2007) with some level of niche adaptation (Merga et al., 2013) and with the ability to survive in the adverse conditions imposed by food processing and storage (Collado and Figueras, 2011; Ferreira et al., 2015; Giacometti et al., 2013; Giacometti et al., 2015; Hausdorf et al., 2013; Rasmussen et al., 2013; Scarano et al., 2014; Serraino and Giacometti, 2014; Shah et al., 2013) that may cause disease through ingestion of contaminated water or food (Collado and Figueras, 2011; Miller et al., 2007).
Source-attribution studies for the burden of human illness require bacterial typing to identify sources and routes of product contamination. Bacterial typing is also a prerequisite for targeted control measures (Dieckmann et al., 2016) and for source-tracking studies to determine the origin of a specific strain by grouping the sources (Santos et al., 2016). The term subtyping refers to characterisation beyond the species or subspecies level, allowing the determination of clonal relationships and the phylogenetic relatedness of bacterial strains (Dieckmann et al., 2016). Nowadays, the genotyping methods most commonly used are based on DNA banding patterns, such as pulsed field gel electrophoresis (PFGE) and amplified fragment length polymorphism (AFLP), PCR-restriction fragment-length polymorphism (RFLP), random amplification of polymorphic DNA (RAPD), enterobacterial repetitive intergenic consensus (ERIC-PCR), multiple locus variable number of tandem repeats analysis (MLVA), multilocus sequence typing (MLST) and 16S rRNA gene sequencing. All these techniques possess different discriminatory powers, and their use depends on the main objective to be achieved. In spite of their recognized resolution, many of these approaches often lack reproducibility within and among laboratories, whereas others are discriminatory and reproducible but expensive, laborious and time-consuming - all undesirable factors for the identification of contamination sources (Santos et al., 2016).
Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has wrought the most radical change in the diagnostic microbiology workflow in the last decade (Fournier et al., 2013) and has become a routine tool for microorganism identification in clinical microbiology laboratories worldwide. However, beyond microbe identification, whose importance for human health care is unquestionable, MALDI-TOF MS has proved to have great potential for epidemiological strain typing and antimicrobial susceptibility/resistance detection (Sanguinetti and Posteraro, 2016). This phenotyping technique is based on the detection of a large number of spectral features originating from proteins, namely highly abundant ribosomal and nucleic acid-binding proteins. Though several attempts have been made to apply MALDI-TOF MS to higher resolution microbial discrimination, they have not yielded uniform success, and the limits of the taxonomic resolution of MALDI-TOF MS profiling might be determined in large part by the nature of the particular bacterium profiled (Ghyselinck et al., 2011; Sandrin et al., 2013). Hence, both the taxonomic resolution of MALDI-TOF MS and whether MALDI-TOF MS analysis will overlap other subtyping techniques need to be evaluated individually for a particular genus or species of interest. No such studies have hitherto been performed on A. butzleri isolates.
The aim of the present study was to evaluate the ability of MALDI-TOF technology to characterize A. butzleri isolates according to their different pattern of TOF peaks, and to perform a comparative analysis of their previously obtained MLST and PFGE profiles (De Cesare et al., 2015; Giacometti et al., 2013).
Section snippets
Strains tested
A set of 104 A. butzleri strains, of which 102 were collected from different sources in an artisanal dairy plant in four samplings in the Emilia Romagna Region between October and December 2012, and the references strains A. butzleri DSM 8739T and A. cryaerophilus DSM 7289T previously characterized by pulsed-field gel electrophoresis (PFGE) (Giacometti et al., 2013) and multilocus sequence typing (MLST) (De Cesare et al., 2015) were selected and analysed. Overall, the strains were obtained from
Results
MALDI-TOF MS correctly identified all 103 A. butzleri strains and 1 A. cryaerophilus strain to species level with score values ≥1.9 using the BRUKER BIOTYPER software.
The dendrogram of all the investigated spectra based on the complete spectra (Fig. 1.) revealed no clearly delineated clusters. Most peaks showed no significant differences among the strains tested, with differences caused only by a few peaks. The following peaks were significant at the Kruskal Wallis test (m/z 2946.81; 2940.78;
Discussion
Microbiological monitoring of food products and the efficiency of early warning systems and outbreak investigations depend on the rapid identification and strain characterisation of pathogens posing risks to the health and safety of consumers (Dieckmann et al., 2016). Although pathogen detection is the first stage of identifying problem areas in a food processing environment or health care system, strain level subtyping is crucial to highlight genotypic differences among strains with particular
Conflict of interest
Katleen Vranckx and Katrien De Bruyne are employees of Applied Maths NV.
Acknowledgments
This research did not receive specific grant from any funding agencies in the public, commercial, or not-for-profit sectors. Anne Collins edited the English manuscript.
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