Recent Advances in Mycotoxin Analysis and Detection of Mycotoxigenic Fungi in Grapes and Derived Products

Mycotoxins are secondary metabolites of filamentous fungi that can cause toxic effects in human and animal health. Most of the filamentous fungi that produce these mycotoxins belong to four genera, namely, Aspergillus, Penicillium, Fusarium, and Alternaria. Mycotoxigenic fungi, along with mycotoxins, create a constant and serious economic threat for agriculture in many terms, counting product losses due to crop contamination and food spoilage, as well malnutrition when considering nutritional quality degradation. Given the importance of robust and precise diagnostics of mycotoxins and the related producing fungi in the grape food chain, one of the most important agricultural sectors worldwide, the present review initially delivers a comprehensive presentation of mycotoxin reports on grape and derived products, including a wide range of commodities such as fresh grapes, raisins, wine, juices, and other processed products. Next, based on worldwide regulations’ requirements for mycotoxins, and referring to the relative literature, this work presents methodological approaches for mycotoxin determination, and stresses major methods for the detection of fungal species responsible for mycotoxin production. The principle of function and basic technical background on the available analytical and molecular biology techniques developed—including chromatography, mass spectrometry, immunochemical-based assays, biosensors, and molecular assays—is briefly given, and references for their application to grape and derived product testing are highlighted

Nanopore-Sequencing Metabarcoding for Identification of Phytopathogenic and Endophytic Fungi in Olive (<i>Olea europaea</i>) Twigs

Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as Cladosporium, Didymosphaeria, Paraconiothyrium, Penicillium, Phoma, Verticillium, and others

Pfcyp51 exclusively determines reduced sensitivity to 14α-demethylase inhibitor fungicides in the banana black Sigatoka pathogen Pseudocercospora fijiensis

The haploid fungus Pseudocercospora fijiensis causes black Sigatoka in banana and is chiefly controlled by extensive fungicide applications, threatening occupational health and the environment. The 14α-Demethylase Inhibitors (DMIs) are important disease control fungicides, but they lose sensitivity in a rather gradual fashion, suggesting an underlying polygenic genetic mechanism. In spite of this, evidence found thus far suggests that P. fijiensis cyp51 gene mutations are the main responsible factor for sensitivity loss in the field. To better understand the mechanisms involved in DMI resistance, in this study we constructed a genetic map using DArTseq markers on two F1 populations generated by crossing two different DMI resistant strains with a sensitive strain. Analysis of the inheritance of DMI resistance in the F1 populations revealed two major and discrete DMI-sensitivity groups. This is an indicative of a single major responsible gene. Using the DMI-sensitivity scorings of both F1 populations and the generation of genetic linkage maps, the sensitivity causal factor was located in a single genetic region. Full agreement was found for genetic markers in either population, underlining the robustness of the approach. The two maps indicated a similar genetic region where the Pfcyp51 gene is found. Sequence analyses of the Pfcyp51 gene of the F1 populations also revealed a matching bimodal distribution with the DMI resistant. Amino acid substitutions in P. fijiensis CYP51 enzyme of the resistant progeny were previously correlated with the loss of DMI sensitivity. In addition, the resistant progeny inherited a Pfcyp51 gene promoter insertion, composed of a repeat element with a palindromic core, also previously correlated with increased gene expression. This genetic approach confirms that Pfcyp51 is the single explanatory gene for reduced sensitivity to DMI fungicides in the analysed P. fijiensis strains. Our study is the first genetic analysis to map the underlying genetic factors for reduced DMI efficacy.</p