Multiplex polymerase chain reaction assays for the detection of the zearalenone chemotype of Fusarium species in white and brown rice

Antagonistic Activity of Oroxylin A against Fusarium graminearum and Its Inhibitory Effect on Zearalenone Production

Fusarium graminearum produces zearalenone (ZEA), a mycotoxin that is widely found in food and feed products and is toxic to humans and livestock. Piper sarmentosum extract (PSE) inhibits F. graminearum, and Oroxylin A appears to be a major antifungal compound in PSE. The aim of this study is to quantify the Oroxylin A content in PSE using UPLC-QTOF-MS/MS, and to investigate the antagonistic activity of Oroxylin A against F. graminearum and its inhibitory effect on ZEA production. The results indicate that Oroxylin A inhibits both fungal growth and ZEA production in a dose-dependent manner. Oroxylin A treatment downregulated the mRNA expression of zearalenone biosynthesis protein 1 (ZEB1) and zearalenone biosynthesis protein 2 (ZEB2). The metabolomics analysis of F. graminearum mycelia indicated that the level of ribose 5-phosphate (R5P) deceased (p < 0.05) after Oroxylin A treatment (64-128 ng/mL). Moreover, as the Oroxylin A treatment content increased from 64 to 128 ng/mL, the levels of cis-aconitate (p < 0.05) and fumarate (p < 0.01) were upregulated successively. A correlation analysis further showed that the decreased R5P level was positively correlated with ZEB1 and ZEB2 expression, while the increased cis-aconitate and fumarate levels were negatively correlated with ZEB1 and ZEB2 expression. These findings demonstrate the potential of Oroxylin A as a natural agent to control toxigenic fungi and their mycotoxin.

Mycotoxins in food and feed: toxicity, preventive challenges, and advanced detection techniques for associated diseases

Mycotoxins are produced primarily as secondary fungal metabolites. Mycotoxins are toxic in nature and naturally produced by various species of fungi, which usually contaminate food and feed ingredients. The growth of these harmful fungi depends on several environmental factors, such as pH, humidity, and temperature; therefore, the mycotoxin distribution also varies among global geographical areas. Various rules and regulations regarding mycotoxins are imposed by the government bodies of each country, which are responsible for addressing global food and health security concerns. Despite this legislation, the incidence of mycotoxin contamination is continuously increasing. In this review, we discuss the geographical regulatory guidelines and recommendations that are implemented around the world to control mycotoxin contamination of food and feed products. Researchers and inventors from various parts of the world have reported several innovations for controlling mycotoxin-associated health consequences. Unfortunately, most of these techniques are restricted to laboratory scales and cannot reach users. Consequently, to date, no single device has been commercialized that can detect all mycotoxins that are naturally available in the environment. Therefore, in this study, we describe severe health hazards that are associated with mycotoxin exposure, their molecular signaling pathways and processes of toxicity, and their genotoxic and cytotoxic effects toward humans and animals. We also discuss recent developments in the construction of a sensitive and specific device that effectively implements mycotoxin identification and detection methods. In addition, our study comprehensively examines the recent advancements in the field for mitigating the health consequences and links them with the molecular and signaling pathways that are activated upon mycotoxin exposure.

An Efficient Strategy Combining Immunoassays and Molecular Identification for the Investigation of Fusarium Infections in Ear Rot of Maize in Guizhou Province, China

Fusarium is one of the most important phytopathogenic and mycotoxigenic fungi that caused huge losses worldwide due to the decline of crop yield and quality. To systematically investigate the infections of Fusarium species in ear rot of maize in the Guizhou Province of China and analyze its population structure, 175 samples of rotted maize ears from 76 counties were tested by combining immunoassays and molecular identification. Immunoassay based on single-chain variable fragment (scFv) and alkaline phosphatase (AP) fusion protein was first employed to analyze these samples. Fusarium pathogens were isolated and purified from Fusarium-infected samples. Molecular identification was performed using the partial internal transcribed spacer (ITS) and translation elongation factor 1α (TEF-1α) sequences. Specific primers were used to detect toxigenic chemotypes, and verification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS). One-hundred and sixty three samples were characterized to be positive, and the infection rate was 93.14%. Sixteen species of Fusarium belonging to six species complexes were detected and Fusarium meridionale belonging to the Fusarium graminearum species complex (FGSC) was the dominant species. Polymerase chain reaction (PCR) identification illustrated that 69 isolates (56.10%) were potential mycotoxin-producing Fusarium pathogens. The key synthetic genes of NIV, NIV + ZEN, DON + ZEN, and FBs were detected in 3, 35, 7, and 24 isolates, respectively. A total of 86.11% of F. meridionale isolates carried both NIV- and ZEN-specific segments, while Fusarium verticillioides isolates mainly represented FBs chemotype. All the isolates carrying DON-producing fragments were FGSC. These results showed that there are different degrees of Fusarium infections in Guizhou Province and their species and toxigenic genotypes display regional distribution patterns. Therefore, scFv-AP fusion-based immunoassays could be conducted to efficiently investigate Fusarium infections and more attention and measures should be taken for mycotoxin contamination in this region.

Distinguishing between long-term-stored and fresh chili pepper powder through fingerprinting of volatiles by headspace capillary-gas chromatography-ion mobility spectrometry

Long-term storage of chili pepper powder results in physicochemical and microbiological changes that decrease its commercial value; these changes occur owing to fungal growth and production of off-flavor compounds. Herein, long-term-stored chili pepper powder (LSCPP) and fresh chili pepper powder (FCPP) were analyzed using internal transcribed spacer sequencing and volatile organic compound fingerprinting by headspace capillary-gas chromatography-ion mobility spectrometry. Fungal analysis detected only Xeromyces bisporus with high accuracy in all the analyzed LSCPP samples. However, the proliferation of X. bisporus on nonspecific spots complicated the distinguishing process between the two groups based solely on fungal analysis. Therefore, nine compounds (three ketones, one alcohol, two aldehydes, one ester, one furan, and one sulfur compound) obtained by autoxidation and fungal metabolism were selected as potential markers for distinguishing LSCPP and FCPP. These above-mentioned substances, which were confirmed as off-flavor species owing to "stale" odor, emitted lipid fragrance and were used to successfully distinguish LSCPP from FCPP using principal component analysis and linear discriminant analysis. PRACTICAL APPLICATION: According to the research results, it was possible to discriminate between long-term stored and fresh chili pepper powders using nine VOC markers for quality control in industry. In addition, the fungus generated from long-term storage of chili pepper powder was Xeromyces bisporus, which was confirmed to be safe for intake because it does not form secondary toxic metabolites.

Sensor Based on Molecularly Imprinted Polymer Membranes and Smartphone for Detection of Fusarium Contamination in Cereals

The combination of the generic mobile technology and inherent stability, versatility and cost-effectiveness of the synthetic receptors allows producing optical sensors for potentially any analyte of interest, and, therefore, to qualify as a platform technology for a fast routine analysis of a large number of contaminated samples. To support this statement, we present here a novel miniature sensor based on a combination of molecularly imprinted polymer (MIP) membranes and a smartphone, which could be used for the point-of-care detection of an important food contaminant, oestrogen-like toxin zearalenone associated with Fusarium contamination of cereals. The detection is based on registration of natural fluorescence of zearalenone using a digital smartphone camera after it binds to the sensor recognition element. The recorded image is further processed using a mobile application. It shows here a first example of the zearalenone-specific MIP membranes synthesised in situ using "dummy template"-based approach with cyclododecyl 2, 4-dihydroxybenzoate as the template and 1-allylpiperazine as a functional monomer. The novel smartphone sensor system based on optimized MIP membranes provides zearalenone detection in cereal samples within the range of 1-10 µg mL^-1 demonstrating a detection limit of 1 µg mL^-1 in a direct sensing mode. In order to reach the level of sensitivity required for practical application, a competitive sensing mode is also developed. It is based on application of a highly-fluorescent structural analogue of zearalenone (2-[(pyrene-l-carbonyl) amino]ethyl 2,4-dihydroxybenzoate) which is capable to compete with the target mycotoxin for the binding to zearalenone-selective sites in the membrane's structure. The competitive mode increases 100 times the sensor's sensitivity and allows detecting zearalenone at 10 ng mL^-1. The linear dynamic range in this case comprised 10-100 ng mL^-1. The sensor system is tested and found effective for zearalenone detection in maize, wheat and rye flour samples both spiked and naturally contaminated. The developed MIP membrane-based smartphone sensor system is an example of a novel, inexpensive tool for food quality analysis, which is portable and can be used for the "field" measurements and easily translated into the practice.

On-line prediction of hazardous fungal contamination in stored maize by integrating Vis/NIR spectroscopy and computer vision

This work presents a fusion scheme to combine visible/near infrared spectroscopy and computer vision for on-line detection of Aspergillus spp. and Fusarium spp. contamination in stored maize. Spectroscopy and image information of 270 groups of maize kernels were collected at speed of 0.15 m/s. Principal component analysis indicated fungi growth on maize could be monitored by both techniques. Spectroscopy method was found sensitive for infection level identification, while computer vision was more effective for fungal strain recognition. Linear discriminant analysis based on fusion of spectral and image features provided 100% accuracy for discrimination of samples infected by different strains after stored for 12 d, which is at least 5.6% higher than single-type features. Classification rate of samples with different infection levels achieved 92.2%, also 5.5% and 10.0% higher than single technique. Moreover, data fusion improved colony counts prediction in samples by partial least squares regression, with root mean-square error of prediction value being reduced by 25.0% and 17.4%, respectively. This study demonstrated the superiority of data fusion for fungal detection in grain during on-line processing.

Electrochemiluminescent competitive immunoassay for zearalenone based on the use of a mimotope peptide, Ru(II)(bpy)3-loaded NiFe2O4 nanotubes and TiO2 mesocrystals

An ultrasensitive competitive-type electrochemiluminescence immunoassay for the mycotoxin zearalenone is described. The method is based on the use of (a) a mimotope peptide that was selected from a phage displayed peptide library and used to substitute ZEN for designing the competitive assay; (b) NiFe₂O₄ nanotubes with large specific surface area loaded with the ECL probe Ru(bpy)₃²⁺; and (c) poly(vinylpyrrolidone) (PVP)-assisted synthesis of TiO₂ mesocrystals that acts as the sensing platform and support for antibody immobilization. Under the optimized conditions and at an ECL working potential of 1.1 V, a linear response is found for ZEN in the 0.1 to 1.0 × 10^-5 ng·mL^-1 concentration range with a detection limit as low as 3.3 fg·mL^-1. Graphical abstract An ultrasensitive competitive-type electrochemiluminescence (ECL) immunosensor based on mimotope peptide was constructed for the detection of Zearalenone.