Application of MALDI-TOF MS fingerprinting as a quick tool for identification and clustering of foodborne pathogens isolated from food products.

Foodborne pathogens can be associated with a wide variety of food products and it is very important to identify them to supply safe food and prevent foodborne infections. Since traditional techniques are timeconsuming and laborious, this study was designed for rapid identification and clustering of foodborne pathogens isolated from various restaurants in Al-Qassim region, Kingdom of Saudi Arabia (KSA) using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Sixty-nine bacterial and thirty-two fungal isolates isolated from 80 food samples were used in this study. Preliminary identification was carried out through culture and BD Phoenix™ methods. A confirmatory identification technique was then performed using MALDI-TOF MS. The BD Phoenix results revealed that 97% (67/69 isolates) of bacteria were correctly identified as 75% Enterobacter cloacae, 95.45% Campylobacter jejuni and 100% for Escherichia coli, Salmonella enterica, Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae. While 94.44% (29/32 isolates) of fungi were correctly identified as 77.77% Alternaria alternate, 88.88% Aspergillus niger and 100% for Aspergillus flavus, Penicillium digitatum, Candida albicans and Debaryomyces hansenii. However, all bacterial and fungal isolates were 100% properly identified by MALDI-TOF MS fingerprinting with a score value ≥2.00. A gel view illustrated that the spectral peaks for the identified isolates fluctuate between 3,000 and 10,000 Da. The results of main spectra library (MSP) dendrogram showed that the bacterial and fungal isolates matched with 19 and 9 reference strains stored in the Bruker taxonomy, respectively. Our results indicated that MALDI-TOF MS is a promising technique for fast and accurate identification of foodborne pathogens.

High-throughput identification of the microbial biodiversity of cocoa bean fermentation by MALDI-TOF MS.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a powerful biotyping tool increasingly used for high-throughput identification of clinical microbial isolates, however, in food fermentation research this approach is still not well established. This study examines the microbial biodiversity of cocoa bean fermentation based on the isolation of micro-organisms in cocoa-producing regions, followed by MALDI-TOF MS in Switzerland. A preceding 6-week storage test to mimic lengthy transport of microbial samples from cocoa-producing regions to Switzerland was performed with strains of Lactobacillus plantarum, Acetobacter pasteurianus and Saccharomyces cerevisiae. Weekly MALDI-TOF MS analysis was able to successfully identify microbiota to the species level after storing live cultures on slant agar at mild temperatures (7°C) and/or in 75% aqueous ethanol at differing temperatures (-20, 7 and 30°C). The efficacy of this method was confirmed by on-site recording of the microbial biodiversity in cocoa bean fermentation in Bolivia and Brazil, with a total of 1126 randomly selected isolates. MALDI-TOF MS analyses revealed known dominant cocoa bean fermentation species with Lact. plantarum and Lactobacillus fermentum in the lactic acid bacteria taxon, Hanseniaspora opuntiae and S. cerevisiae in the yeast taxon, and Acet. pasteurianus, Acetobacter fabarum, Acetobacter ghanensis and Acetobacter senegalensis in the acetic acid bacteria taxon. SIGNIFICANCE AND IMPACT OF THE STUDY: Microbial identification with MALDI-TOF MS has increased the number of samples that can be analysed in a given time, a prerequisite for high-throughput methods. This method is already widely used for the identification of clinical microbial isolates, whereas in food fermentation research, including cocoa bean fermentation, microbiota is mostly identified by time-consuming, biochemical-based phenotyping and molecular approaches. This study presents the use of MALDI-TOF MS for characterizing the microbial biodiversity of cocoa bean fermentation. The feasibility of MALDI-TOF MS identification of cocoa-specific microbiota has been shown with samples collected during on-site studies in two countries of origin, Bolivia and Brazil.

Optimization of experimental and modelling parameters for the differentiation of beverage spoiling yeasts by Matrix-Assisted-Laser-Desorption/Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) in response to varying growth conditions.

The growth of spoiling yeasts in beverages results in reduced quality, economic and image losses. Therefore, biochemical and DNA-based identification methods have been developed but are mostly time-consuming and laborious. Matrix-Assisted-Laser-Desorption/Ionization-Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) could deliver discriminative peptide mass fingerprints within minutes and could thus be a rapid and reliable tool for identification and differentiation. However, routine analysis of yeasts by MALDI-TOF MS is yet impaired by low reproducibility and effects of different physiological states of organisms on the reliability of the identification method are still controversial. The aim of this study was to optimize sample preparation and measurement parameterization using three spoilage yeasts (Saccharomyces cerevisiae var. diastaticus, Wickerhamomyces anomalus and Debaryomyces hansenii). The influence of environmental or physiological parameters including oxygen availability, different nutrients, cell density and growth phase were analysed and revealed small differences in mass fingerprints. Yeasts grown in the presence or absence of oxygen were precisely differentiated along these differences in mass fingerprints and a crude classification of growth phase was possible. Cell concentration did not affect the spectra distinctly, neither qualitatively nor quantitatively, and an influence of available nutrients could not be measured in each case. However, core mass peaks remained constant under all tested conditions enabling reliable identification.