A novel library-independent approach based on high-throughput cultivation in Bioscreen and fingerprinting by FTIR spectroscopy for microbial source tracking in food industry.

Microbiological source tracking (MST) for food industry is a rapid growing area of research and technology development. In this paper, a new library-independent approach for MST is presented. It is based on a high-throughput liquid microcultivation and FTIR spectroscopy. In this approach, FTIR spectra obtained from micro-organisms isolated along the production line and a product are compared to each other. We tested and evaluated the new source tracking approach by simulating a source tracking situation. In this simulation study, a selection of 20 spoilage mould strains from a total of six genera (Alternaria, Aspergillus, Mucor, Paecilomyces, Peyronellaea and Phoma) was used. The simulation of the source tracking situation showed that 80-100% of the sources could be correctly identified with respect to genus/species level. When performing source tracking simulations, the FTIR identification diverged for Phoma glomerata strain in the reference collection. When reidentifying the strain by sequencing, it turned out that the strain was a Peyronellaea arachidicola. The obtained results demonstrated that the proposed approach is a versatile tool for identifying sources of microbial contamination. Thus, it has a high potential for routine control in the food industry due to low costs and analysis time. SIGNIFICANCE AND IMPACT OF THE STUDY: The source tracking of fungal contamination in the food industry is an important aspect of food safety. Currently, all available methods are time consuming and require the use of a reference library that may limit the accuracy of the identification. In this study, we report for the first time, a library-independent FTIR spectroscopic approach for MST of fungal contamination along the food production line. It combines high-throughput microcultivation and FTIR spectroscopy and is specific on the genus and species level. Therefore, such an approach possesses great importance for food safety control in food industry.

FTIR spectroscopic characterization of differently cultivated food related yeasts.

The application of Fourier Transform Infrared Spectroscopy for characterization of yeasts is growing rapidly. Since it is known that the phenotypic expression of yeast cells depends sensitively on the nutrients that are available in the growth medium, one standardized growth medium is usually used for identification and characterization purposes in order to obtain reproducible FTIR signals. Since our recently developed high-throughput micro-cultivation protocol has the capacity to use more than one standardized growth medium, we wanted to investigate if the parallel use of multiple growth media can improve identification results. For this purpose, five different cultivation media (YP, YPD, YMB, SAB and SD) were used. In total 91 food spoilage yeast strains of 12 different genera were cultivated in different cultivation media and subsequently characterized by FTIR spectroscopy. For spectral identifications, Radial Basis Function-Partial Least Squares (RBF-PLS) was used in combination with cross-model validation where an inner cross-validation loop was used to optimize the model, while in an outer loop an independent test set was kept aside to test the optimized model. Sensitivity and specificity were evaluated for each studied genus class. The results show that the YMB selective medium gave the best discrimination results for 9 of the 12 genera with sensitivity above 90%. Only three genera showed better identification results on other media (Clavispora and Metschnikowia on medium SD, Debaryomyces on medium YPD). We therefore suggest to use the media SD, YPD in combination with the YMB medium for the identification of food spoilage yeasts.

Characterization of food spoilage fungi by FTIR spectroscopy.

AIMS: The objective of the study was to evaluate a high-throughput liquid microcultivation protocol and FTIR spectroscopy for the differentiation of food spoilage filamentous fungi. METHODS AND RESULTS: For this study, fifty-nine food-related fungal strains were analysed. The cultivation of fungi was performed in liquid medium in the Bioscreen C microtitre plate system with a throughput of 200 samples per cultivation run. Mycelium was prepared for FTIR analysis by a simple procedure, including a washing and a homogenization step. Hierarchical cluster analysis was used to study affinity among the different species. Based on the hierarchical cluster analysis, a classification and validation scheme was developed by artificial neural network analysis. The classification network was tested by an independent test set. The results show that 93.9 and 94.0% of the spectra were correctly identified at the species and genus level, respectively. CONCLUSIONS: The use of high-throughput liquid microcultivation protocol combined with FTIR spectroscopy and artificial neural network analysis allows differentiation of food spoilage fungi on the phylum, genus and species level. SIGNIFICANCE AND IMPACT OF THE STUDY: The high-throughput liquid microcultivation protocol combined with FTIR spectroscopy can be used for the detection, classification and even identification of food-related filamentous fungi. Advantages of the method are high-throughput characteristics, high sensitivity, low costs and relatively short time of analysis.