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 93Á9 and 94Á0% 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.

A meat factory commensal bacterium, Acinetobacter calcoaceticus, affected the spatial distribution of Escherichia coli O157:H7 surface colonization. The biovolume of E. coli O157:H7 was 400-fold higher (1.2 ؋ 10 6 m 3 ) in a dynamic cocultured biofilm than in a monoculture (3.0 ؋ 10 3 m 3 ), and E. coli O157:H7 colonized spaces between A. calcoaceticus cell clusters.

Characterization and identification of fungi in food industry is an important issue both for routine analysis and trouble-shooting incidences. Present microbial techniques for fungal characterization suffer from a low throughput and are time consuming. In this study we present a protocol for high-throughput microcultivation and spectral characterization of fungi by Fourier transform infrared spectroscopy. For the study 11 species of in total five different fungal genera (Alternaria, Aspergillus, Mucor, Paecilomyces, and Phoma) were analyzed by FTIR spectroscopy. All the strains were isolated from trouble-shooting incidents in the production of low and high acid beverages. The cultivation was performed in malt extract broth (liquid medium) in a Bioscreen C system, allowing high-throughput cultivation of 200 samples at the same time. Mycelium was subsequently investigated by high-throughput Fourier transform infrared spectroscopy. Four spectral regions, fatty acids + lipid (3200-2800 cm(-1), 1300-1000 cm(-1)), protein-lipid (1800-1200 cm(-1)), carbohydrates (1200-700 cm(-1)) and "finger print" (900-700 cm(-1)) were evaluated for reproducibility and discrimination ability. The results show that all spectral regions evaluated can be used as spectroscopic biomarkers for differentiation of fungi by FTIR. The influence of different growth times on the ability of species discrimination by FTIR spectroscopy was investigated, and an optimal separation of all five genera was observed after five days of growth. This work presents a novel concept for high-throughput cultivation of fungi for FTIR spectroscopy that enables characterization or identification of hundreds of strains per day.