Comparison of different methods for the recovery of DNA from spores of mycotoxin-producing moulds in spiked food samples

Early detection of Botrytis cinerea in strawberry fruit during quiescent infection using selected ion flow tube mass spectrometry (SIFT-MS)

Botrytis cinerea is a devastating pathogen that can cause huge postharvest losses of strawberry. Although this fungus usually infects strawberries through their flowers, symptoms mainly appear when fruit are fully mature. A fast and sensitive method to detect and quantify the fungal infection, prior to symptom development, is, therefore, needed. In this study, we explore the possibility of using the strawberry volatilome to identify biomarkers for B. cinerea infection. Strawberry flowers were inoculated with B. cinerea to mimic the natural infection. First, quantitative polymerase chain reaction (qPCR) was used to quantify B. cinerea in the strawberry fruit. The detection limit of qPCR for B. cinerea DNA extracted from strawberries was 0.01 ng. Subsequently, changes in the fruit volatilome at different fruit developmental stages were characterized using gas chromatography - mass spectrometry (GC-MS) and selected ion flow tube mass spectrometry (SIFT-MS). Based on GC-MS data, 1-octen-3-ol produced by B. cinerea was confirmed as a potential biomarker of B. cinerea infection. Moreover, the product ion NO⁺ 127, obtained by SIFT-MS measurements, was proposed as a potential biomarker for B. cinerea infection by comparing its relative level with that of 1-octen-3-ol (obtained by GC-MS) and B. cinerea (obtained by qPCR). Separate PLS regressions were carried out for each developmental stages, and 11 product ions were significantly altered at all developmental stages. Finally, PLS regressions using these 11 ions as variables allowed the discrimination between samples containing different amount of B. cinerea. This work showed that profiling the fruit's volatilome using SIFT-MS can be used as a potential alternative to detect B. cinerea during the quiescent stage of B. cinerea infection prior to symptom development. Moreover, the corresponding compounds of potential biomarkers suggest that the volatile changes caused by B. cinerea infection may contribute to strawberry defense.

Are antimicrobial resistance genes key targets to detect genetically modified microorganisms in fermentation products?

As genetically modified microorganisms (GMM), commonly used by the food and feed industry to produce additives, enzymes and flavourings, are frequently harbouring antimicrobial resistance (AMR) genes as selection markers, health and environmental concerns were consequently raised. For this reason, the interest of the competent authorities to control such microbial fermentation products has strongly increased, especially since several recent accidental contaminations of unauthorized GMM, or associated recombinant DNA, in bacterial fermentation products intended for the European food and feed chain. However, no global screening strategy is currently available in enforcement laboratories to assess the presence of GMM harbouring AMR genes and/or the presence of full-length AMR genes. Moreover, the confidentiality of the related GMM dossiers strongly hampers the development of methods to perform such control. To overcome this issue, an analysis of related publicly available patents was performed in this study to identify all reported AMR genes. On this basis, the aminoglycoside adenyltransferase (aadD) gene, conferring a resistance to both kanamycin and neomycin, was identified as a key target to cover a large spectrum of GM bacteria. A real-time PCR method to screen for its potential presence as well as a nested-PCR method associated with a sequencing analysis to assess its full-length were developed to target this aadD gene. The performance of these new methods were successfully evaluated in terms of specificity, sensitivity and applicability, allowing their easy implementation in enforcement laboratories. Moreover, the integration of these newly developed methods to our very recently proposed strategy, initially targeting GMM carrying a chloramphenicol resistance gene, allows to drastically increase the detection spectrum of GM bacteria producing fermentation food and feed products. The data generated by the proposed strategy represents therefore a crucial support for the competent authorities, especially to evaluate potential risks for the food and feed safety.

Mould spoilage of foods and beverages: Using the right methodology

Fungal spoilage of products manufactured by the food and beverage industry imposes significant annual global revenue losses. Mould spoilage can also be a food safety issue due to the production of mycotoxins by these moulds. To prevent mould spoilage, it is essential that the associated mycobiota be adequately isolated and accurately identified. The main fungal groups associated with spoilage are the xerophilic, heat-resistant, preservative-resistant, anaerobic and psychrophilic fungi. To assess mould spoilage, the appropriate methodology and media must be used. While classic mycological detection methods can detect a broad range of fungi using well validated protocols, they are time consuming and results can take days or even weeks. New molecular detection methods are faster but require good DNA isolation techniques, expensive equipment and may detect viable and non-viable fungi that probably will not spoil a specific product. Although there is no complete and easy method for the detection of fungi in food it is important to be aware of the limitation of the methodology. More research is needed on the development of methods of detection and identification that are both faster and highly sensitive.