MALDI-TOF MS Fingerprinting for the Detection of Bacterial Food Contaminants

Most reviews and studies that have been published about MALDI-TOF MS fingerprinting for bacterial identification have been aimed at application to the clinical sector and the routine identification of human pathogens in clinical isolates. Nevertheless, as mentioned before, many bacterial foodborne pathogens cause human infectious diseases and are therefore included in these studies, such as Bacillus spp., Escherichia coli, Listeria spp., Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella enterica, Staphylococcus aureus, and Streptococcus spp. (Farfour et al., 2012; Hsieh et al., 2008; Smole et al., 2002). In Table 2.1 studies based on MALDI-TOF MS analysis of bacterial species with foodborne pathogenic character are listed. Recently, the fast, accurate, and easy-to-handle MALDI-TOF MS fingerprinting technology has also been applied to bacterial identification in veterinary diagnostics, environmental isolates, and food samples. Mazzeo et al. (2006) and Bohme et al. (2013)

Scheme of the bacterial identification process by MALDI-TOF MS fingerprinting

FIGURE 2.1 Scheme of the bacterial identification process by MALDI-TOF MS fingerprinting.

constructed spectral libraries containing spectra of 24 and 58 foodborne bacterial species, respectively. Mazzeo et al. (2006) made the spectral profiles and peak mass lists freely available on the Web ( Descr_Bact_Dbase.htm). The library includes the genera Escherichia, Yersinia, Proteus, Morganella, Salmonella, Staphylococcus, Micrococcus, Lactococcus, Pseudomonas, Leuconostoc, and Listeria. Bohme et al. (2013) created the spectral library SpectraBank (, where other researchers can download spectral information of 58 bacterial species that are of interest for food safety and quality, including the genera Acinetobacter, Aeromonas, Bacillus, Carnobacterium, Clostridium, Listeria, Photobacterium, Pseudomonas, Stenotrophomonas, Shewanella, Staphylococcus, Vibrio, and a number of genera of the Enterobacteriaceae family.

In a further study, histamine-producing bacterial species have successfully been differentiated by MALDI-TOF MS fingerprinting (Fernandez-No et al., 2010).

In most studies, MALDI-TOF MS analysis has been applied to bacterial reference strains. Although these strains correspond to bacterial species for which the pathogenic potential is known, it has been shown that real isolates can differ significantly from type strains in their phenotypic and proteotypic properties, due to modifications caused by environmental changes or the food matrices. To perform efficient bacterial species identification of foodborne pathogens that are isolated from food products, it is important to include spectral information of strains isolated from different food matrices into the databases. Therefore, for subtyping of Yersinia enterocolitica (Stephan et al., 2011) and E. coli (Novais et al., 2014) a few strains isolated from food products have been included. Likewise, four strains isolated from food have been studied for species level differentiation of Bacillus pumilus and Bacillus safensis (Branquinho et al., 2014). Dubois et al. (2010) studied 92 Staphylococcus spp. strains isolated from food and plants in relation to species identification inside the genus Staphylococcus (Dubois et al., 2010). In further studies, Dieckmann et al. (2011) analyzed S. enterica subsp. enterica, Aeromonas spp., and Vibrio spp. strains, including isolates from food, environment, animals, and humans. Cronobacter sakazakii is getting attention as an emerging food- borne pathogen and due to its presence in infant formulas. MALDI-TOF MS has been successfully applied to identify Cronobacter spp. strains at the species level with high accuracy. In these studies, besides reference strains, strains have been isolated from infant formulas, milk powder producing plants, and further food samples (Stephan et al., 2010; Zhu et al., 2011). Vibrio parahaemolyticus is a main causative agent of pandemic outbreaks of seafood-borne gastroenteritis. MALDI-TOF MS has been applied to distinguish V. parahaemolyticus from other Vibrio spp. For this, V. parahaemolyticus strains have been isolated from illness- related human and food samples of diverse outbreaks and analyzed by

MALDI-TOF MS (Hazen et al., 2009). A new approach for the rapid identification of Listeria monocytogenes has been described by Jadhav et al. (2014). Isolates from different food products (UHT milk, cheese, chicken pate, and cantaloupe), spiked with bacterial pathogens, have been submitted directly to analysis in selective enrichment broth, after incubation of 30 h (24 h first enrichment and additional enrichment of 6 h). This methodology represents a fast and simple way to identify L. monocytogenes at very low concentrations in food products. MALDI-TOF MS has been successfully applied to the differentiation of the closely related species Streptococcus uberis and Streptococcus parauberis and to the correct identification of two S. parauberis strains isolated from vacuum-packaging refrigerated seafood products (Fernandez-No et al., 2012). Some species of the genus Streptococcus are of special interest for the dairy industrial sector, since they are important mastitis-causing agents. In this sense, MALDI-TOF MS has been successfully applied to differentiate mastitis- causing Streptococcus spp. strains, isolated from mastitis causes, blood and food at the species and subspecies level (Raemy et al., 2013; Schabauer et al., 2014). Finally, in a number of studies of Bohme et al. the ability of MALDI-TOF MS fingerprinting in identification of bacterial strains isolated from seafood products has been tested. For that, a total of 50 bacterial strains have been isolated from different fish and processed seafood products.

In general, MALDI-TOF mass spectral profiles exhibit a high interspecific variability and at the same time a high intraspecific similarity for most bacterial species, allowing identification at the genus and species levels. Exceptions have been reported for some very closely related species, such as Escherichia coli and Shigella spp., Streptococcus spp., and Listeria spp. that could not be differentiated by the commonly applied databases at the species level (Farfour et al., 2012; Risch et al., 2010). Nevertheless, MALDI-TOF MS demonstrated a high discriminatory potential at the intraspecies level. The differentiation of subspecies and serotypes is of crucial importance for risk assessment in the food sector, due to the varying pathogenic character. Likewise, determination of clonal lineages is fundamental for epidemiological studies of foodborne disease outbreaks. Clustering of mass spectral data has been successfully applied for chemotaxonomic studies of bacterial strains and compared to phylogenetic trees based on DNA analysis. The high similarity observed is not surprising, since the molecules detected by MALDI-TOF MS are generally attributed to ribosomal proteins that serve as taxonomic markers for the corresponding genus, species, or strain (Welker and Moore, 2011). In addition, in many cases a higher discriminatory potential has been observed for the proteomic approach when compared to conventional bacterial classification tools (Bohme et al., 2013; Risch et al., 2010). Recent reviews pay special attention to MALDI-TOF MS applications as a bacterial typing tool, with the aim of detecting antimicrobial resistance and carrying out epidemiological studies (Clark et al., 2013; Sandrin et al., 2013). In some cases, the available spectral databases do not exhibit sufficient resolution at the species, subspecies or strain levels to perform bacterial typing of serotypes, pathotypes, or clonal lineages. Thus, the use of bioinformatics tools and the determination of subtype-specific biomarker peaks is required (Suarez et al., 2013). In this sense, subtyping of Y. enterocolitica (Stephan et al., 2011) and Yersinia pestis (Ayyadurai et al., 2010) strains into different serotypes could be achieved. Likewise, strains of the highly infective Campylobacter jejuni have been classified by MALDI-TOF MS, resulting in the separation of hyperinvasive strains and strains with an extended amino acid metabolism from the other strains (Mandrell et al., 2005). A critical aspect for E. coli identification is the high similarity to Shigella spp. The differentiation of E. coli and Shigella spp. by MALDI- TOF MS has been demonstrated recently by determining 15 biomarker peaks with the ClinProTool from Bruker (Khot and Fisher, 2013). A further challenge is the bacterial typing of E. coli isolates and differentiation of clonal groups to realize epidemiological studies. In a number of studies, MALDI- TOF MS has been successfully applied to the differentiation of E. coli clones (Christner et al., 2014; Matsumura et al., 2014; Novais et al., 2014). In these studies, clonal groups related to extended-spectrum-(3-lactamase (ESBL) producers have been identified at high percentages. Likewise, in the spectral profiles of the Shiga-Toxigenic E. coli O104:H4 two peaks have been determined that were not present in the spectra of preoutbreak strains. MALDI- TOF MS has also been successfully applied for discrimination of the five most important serovars of S. enterica subsp. enterica based on a decision tree and specific biomarkers (Dieckmann and Malorny, 2011). In another study, the differentiation of S. enterica typhy from nontyphy was not possible with the Biotyper database, but clear identification could be achieved after identifying serovar-specific biomarkers (Kuhns et al., 2012).

MST aims at the detection of foodborne pathogens in the food chain and determination of the source of contamination and consequent corrective actions to be taken, as well as prevention of foodborne outbreaks. MALDI- TOF MS fingerprinting has been successfully applied to analyze Enterococcus faecium and Enterococcus faecalis and differentiate the strains in relation to their isolation sources (meat or dairy products) (Quintela-Baluja et al., 2013). Similarly, spectral variability could be observed at the strain level in relation to the geographical origin and moment of isolation of V. paraheamolyticus strains (Hazen et al., 2009).

High interest exists in the ability to distinguish methicillin-resistant S. aureus strains (MRSA) from methicillin-sensitive S. aureus strains (MSSA). MALDI-TOF MS fingerprinting has been successfully applied to this matter and was also able to distinguish clonal types of S. aureus (Du et al., 2002; Jackson et al., 2005; Wolters et al., 2010). The analysis of MRSA strains isolated during an outbreak allowed differentiation from

MSSA strains, as well as rapid typing of the outbreak strains and detection of epidemic lineages (Josten et al., 2013). In Fig. 2.2, spectral differences observed for S. aureus at the strain level are highlighted. The corresponding study demonstrated the discriminatory potential of MALDI-TOF MS, since the studied strains exhibited 100% identical 16S rRNA gene sequences, but could be classified into subgroups by the spectral profiles (Bohme, Morandi, et al., 2012b). Nevertheless, the subtypes could not be related to the production of toxins, as also confirmed by further studies (Szabados et al., 2010).

Spectral profiles of different S. aureus strains. Symbols correspond to species- specific (?), subgroup-specific (*), and further characteristic peaks (o)

FIGURE 2.2 Spectral profiles of different S. aureus strains. Symbols correspond to species- specific (?), subgroup-specific (*), and further characteristic peaks (o).

The genus Bacillus is known to comprise closely related species, with differentiation by DNA-based approaches not always possible. However, the different species corresponding to the Bacillus cereus/thurin- giensis and the Bacillus subtilis/amyloliquefaciens complexes exhibit very different pathogenic and spoilage potential, thus requiring their correct identification. With MALDI-TOF MS and cluster analysis, a clear grouping of the B. subtilis strains was achieved (Bohme et al., 2013). In the case of B. cereus and B. thuringiensis, the 16S rRNA sequences are nearly 100% identical, inhibiting any differentiation at the species level. By phyloproteo- mic clustering, the strains could not be identified; however, a differentiation of the strains into subgroups was obtained. These findings were confirmed in a further study, where a number of Bacillus spp. strains, isolated from fresh and processed food products, were analyzed by MALDI-TOF MS (Fernandez-No et al., 2013).

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