Rapid Detection of Mycotoxin Contamination 2.0

A special issue of Toxins (ISSN 2072-6651). This special issue belongs to the section "Mycotoxins".

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 9067

Special Issue Editor


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Guest Editor
Agro-Environmental Research Centre, Institute of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, Herman O. u. 15, H-1022 Budapest, Hungary
Interests: environmental and food safety; organic microcontaminants (pesticide residues and mycotoxins); environmental analysis; agricultural ecotoxicology; genetic safety
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Special Issue Information

Dear Colleagues,

Upon the success of our previous Special Issue, Rapid Detection of Mycotoxin Contamination (https://www.mdpi.com/journal/toxins/special_issues/Detection_Mycotoxin_Contamination), which was launched at the end of 2018 and completed at the end of 2020, we would like to continue to cover the topic with reports of upcoming developments in the field.

Mycotoxin contamination in crops and subsequent mycotoxin contamination in food and feed is currently a major concern in environmental and food safety, affecting both crop production and animal husbandry. In turn, the rapid detection of mycotoxin levels in food, feed, and other biological and environmental matrices is of key importance both in mycotoxin monitoring and in exposure assessment.

A newly identified and emerging matrix for mycotoxin contamination is surface and drinking water, where mycotoxins can emerge upon the infestation of toxinogenic fungi, upon leaching from infested soil as water runoff from agriculture, or upon washing out from contaminated agricultural commodities. In turn, mycotoxins may present threats for drinking water quality, and their analysis in aqueous environments is therefore also emphasized.

Mycotoxin occurrence in produce is mostly due to improper harvest or storage conditions that favour the emergence of toxinogenic fungi (e.g., Fusarium, Penicillium, Aspergillus and other species). Target mycotoxins include the most hazardous aflatoxins, trichothecenes (e.g., T-2, deoxynivalenol), resorcilactones (e.g., zearalenone), fumonisins and ochratoxins, as well as recently identified compounds such as sterigmatocystin, moniliformin and others. Meteorological conditions prior to harvest strongly affect fungal growth and mycotoxin production; climate change also exerts its impacts, as toxinogenic fungal strains may now emerge in climatic zones they could not previously colonise.

Our Special Issue of Toxins aims to summarise the importance of mycotoxin detection in various matrices by reporting diverse aspects, hopefully covering a wide range of applications, including but not limited to:

- Monitoring the occurrence of mycotoxins in crops and produce as related to meteorological conditions, including the assessment of the potential effects of climate change trends on mycotoxin occurrence;

- A particular issue related to the above point is the general and repeatedly refuted allegation of ecological farming of being a source of mycotoxin contamination due to prohibition of the use of synthetic fungicides, therefore, submission of comparative monitoring studies of mycotoxins in conventional and ecological agriculture are welcome;

- Decomposition of mycotoxins in biological matrices due to the effects of natural or artificially accelerated enzymatic conditions;

- Effect-based monitoring of mycotoxins in affected animals, as well as veterinary mycotoxin analyses;

- Assessment of mycotoxin decontamination methods aiming to suppress emerging mycotoxin poisoning;

- Novel or inventive methods of mycotoxin analysis including chromatography, immunoassay, molecular biology, sensorics and other means, including novel sample preparation methods (e.g., QuEChERS, immunoaffinity pre-purification);

- Methods of toxicological or ecotoxicological assessment, including cytotoxicity, genotoxicity, mutagenicity and endocrine disruption, combined with chemical analysis.

Prof. Dr. András Székács
Guest Editor

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Keywords

  • mycotoxin analysis
  • monitoring
  • decomposition
  • metabolism
  • decontamination
  • instrumental analysis
  • immunoanalysis
  • sensorics
  • ecotoxicological assessment
  • cytotoxicity
  • genotoxicity
  • mutagenicity
  • endocrine disruption

Published Papers (4 papers)

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Research

14 pages, 1718 KiB  
Article
Optimization and Validation of Dispersive Liquid–Liquid Microextraction for Simultaneous Determination of Aflatoxins B1, B2, G1, and G2 in Senna Leaves and Pods Using HPLC-FLD with Pre-Column Derivatization
by Thanapoom Maneeboon, Chananya Chuaysrinule and Warapa Mahakarnchanakul
Toxins 2023, 15(4), 277; https://doi.org/10.3390/toxins15040277 - 7 Apr 2023
Cited by 3 | Viewed by 1784
Abstract
Dispersive liquid–liquid microextraction (DLLME) was optimized for the simultaneous extraction of aflatoxins (AFB1, AFB2, AFG1, and AFG2) from powdered senna leaves and pods. Detection was performed using high-performance liquid chromatography with fluorescence detection (HPLC-FLD) and pre-column derivatization. The parameters affecting the DLLME extraction [...] Read more.
Dispersive liquid–liquid microextraction (DLLME) was optimized for the simultaneous extraction of aflatoxins (AFB1, AFB2, AFG1, and AFG2) from powdered senna leaves and pods. Detection was performed using high-performance liquid chromatography with fluorescence detection (HPLC-FLD) and pre-column derivatization. The parameters affecting the DLLME extraction efficiency were evaluated. Chloroform (200 µL) was used as an extraction solvent, 500 µL of distilled water was used as a dispersive solvent, and the extraction was performed at pH 5.6 with no salt added. The optimized method was validated using leaves and pods according to the European Commission guidelines. The linear range for all aflatoxins was 2–50 µg/kg, with values for regression coefficients of determination exceeding 0.995. The recoveries of spiked senna leaves and pods were in the ranges of 91.77–108.71% and 83.50–102.73%, respectively. The RSD values for intra-day and inter-day precisions were in the ranges of 2.30–7.93% and 3.13–10.59%, respectively. The limits of detection and quantification varied in the ranges of 0.70–1.27 µg/kg and 2.13–3.84 µg/kg, respectively. The validated method was successfully applied for the quantification of aflatoxins in 60 real samples of dried senna leaves and pods. Full article
(This article belongs to the Special Issue Rapid Detection of Mycotoxin Contamination 2.0)
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15 pages, 636 KiB  
Article
Advantages of Multiplexing Ability of the Orbitrap Mass Analyzer in the Multi-Mycotoxin Analysis
by Dávid Rakk, József Kukolya, Biljana D. Škrbić, Csaba Vágvölgyi, Mónika Varga and András Szekeres
Toxins 2023, 15(2), 134; https://doi.org/10.3390/toxins15020134 - 7 Feb 2023
Cited by 5 | Viewed by 1673
Abstract
In routine measurements, the length of the analysis time and nfumber of samples analysed during a time unit are crucial parameters, which are especially important for the food analysis, particularly in the case of mycotoxin determinations. High-resolution equipment, including time-of-flight or Orbitrap analyzators, [...] Read more.
In routine measurements, the length of the analysis time and nfumber of samples analysed during a time unit are crucial parameters, which are especially important for the food analysis, particularly in the case of mycotoxin determinations. High-resolution equipment, including time-of-flight or Orbitrap analyzators, can provide stable instrumental background for high-throughput analyses. In this report, a short, 1 min MS-based multi-mycotoxin method was developed with the application of a short column as a reduced chromatographic separation, taking advantages of the multiplexing and high-resolution capability of the QExactive Orbitrap MS possessing sub-1 ppm mass accuracy. The performance of the method was evaluated regarding selectivity, LOD, LOQ, linearity, matrix effect, and recovery, and compared to a UHPLC-MS/MS method. The final multiplexing method was able to quantify 11 mycotoxins in defined ranges (aflatoxins (corn, 2.8–600 μg/kg; wheat, 1.5–350 μg/kg), deoxynivalenol (corn, 640–9600 μg/kg; wheat, 128–3500 μg/kg), fumonisins (corn, 20–1500 μg/kg; wheat, 30–3500 μg/kg), HT-2 (corn, 64–5200 μg/kg; wheat, 61–3500 μg/kg), T-2 (corn, 10–800 μg/kg; wheat, 4–250 μg/kg), ochratoxin (corn, 4.7–600 μg/kg; wheat, 1–1000 μg/kg), zearalenone (corn, 64–4800 μg/kg; wheat, 4–500 μg/kg)) within one minute in corn and wheat matrices at the MRL levels stated by the European Union. Full article
(This article belongs to the Special Issue Rapid Detection of Mycotoxin Contamination 2.0)
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15 pages, 2595 KiB  
Article
Development of an Immunofluorescent Capillary Sensor for the Detection of Zearalenone Mycotoxin
by Krisztina Majer-Baranyi, Attila Barócsi, Patrik Gádoros, László Kocsányi, András Székács and Nóra Adányi
Toxins 2022, 14(12), 866; https://doi.org/10.3390/toxins14120866 - 9 Dec 2022
Cited by 1 | Viewed by 1400
Abstract
A capillary-based immunofluorescence sensor was developed and incorporated in a flow injection analysis system. The light-guiding capillary was illuminated axially by a 473 nm/5 mW solid state laser through a tailored optofluidic connector. High sensitivity of the system was achieved by efficiently collecting [...] Read more.
A capillary-based immunofluorescence sensor was developed and incorporated in a flow injection analysis system. The light-guiding capillary was illuminated axially by a 473 nm/5 mW solid state laser through a tailored optofluidic connector. High sensitivity of the system was achieved by efficiently collecting and detecting the non-guided fluorescence signal scattered out along the wall of the capillary. The excitation was highly suppressed with bandpass and dichroic filters by simultaneously exploiting the guiding effect inside the capillary. The glass capillary used as a measuring cell was silanized in liquid phase by 3-aminopropyltriethoxysilane (APTS), and the biomolecules were immobilized using glutaraldehyde inside the capillary. The applicability of the developed system was tested with a bovine serum albumin (BSA)—anti-BSA-IgG model-molecule pair, using a fluorescently labeled secondary antibody. Based on the results of the BSA–anti-BSA experiments, a similar setup using a primary antibody specific for zearalenone (ZON) was established, and a competitive fluorescence measurement system was developed for quantitative determination of ZON. For the measurements, 20 µg/mL ZON-BSA conjugate was immobilized in the capillary, and a 1:2500 dilution of the primary antibody stock solution and a 2 µg/mL secondary antibody solution were set. The developed capillary-based immunosensor allowed a limit of detection (LOD) of 0.003 ng/mL and a limit of quantification (LOQ) of 0.007 ng/mL for ZON in the competitive immunosensor setup, with a dynamic detection range of 0.01–10 ng/mL ZON concentrations. Full article
(This article belongs to the Special Issue Rapid Detection of Mycotoxin Contamination 2.0)
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22 pages, 1652 KiB  
Article
A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy
by Francesca Ghilardelli, Mario Barbato and Antonio Gallo
Toxins 2022, 14(5), 323; https://doi.org/10.3390/toxins14050323 - 3 May 2022
Cited by 7 | Viewed by 3428
Abstract
Mycotoxins should be monitored in order to properly evaluate corn silage safety quality. In the present study, corn silage samples (n = 115) were collected in a survey, characterized for concentrations of mycotoxins, and scanned by a NIR spectrometer. Random Forest classification models [...] Read more.
Mycotoxins should be monitored in order to properly evaluate corn silage safety quality. In the present study, corn silage samples (n = 115) were collected in a survey, characterized for concentrations of mycotoxins, and scanned by a NIR spectrometer. Random Forest classification models for NIR calibration were developed by applying different cut-offs to classify samples for concentration (i.e., μg/kg dry matter) or count (i.e., n) of (i) total detectable mycotoxins; (ii) regulated and emerging Fusarium toxins; (iii) emerging Fusarium toxins; (iv) Fumonisins and their metabolites; and (v) Penicillium toxins. An over- and under-sampling re-balancing technique was applied and performed 100 times. The best predictive model for total sum and count (i.e., accuracy mean ± standard deviation) was obtained by applying cut-offs of 10,000 µg/kg DM (i.e., 96.0 ± 2.7%) or 34 (i.e., 97.1 ± 1.8%), respectively. Regulated and emerging Fusarium mycotoxins achieved accuracies slightly less than 90%. For the Penicillium mycotoxin contamination category, an accuracy of 95.1 ± 2.8% was obtained by using a cut-off limit of 350 µg/kg DM as a total sum or 98.6 ± 1.3% for a cut-off limit of five as mycotoxin count. In conclusion, this work was a preliminary study to discriminate corn silage for high or low mycotoxin contamination by using NIR spectroscopy. Full article
(This article belongs to the Special Issue Rapid Detection of Mycotoxin Contamination 2.0)
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