Universal screening of 200 mycotoxins and their variations in stored cereals in Shanghai, China by UHPLC-Q-TOF MS

Exploring the potential of microscopic hyperspectral, Raman, and LIBS for nondestructive quality assessment of diverse rice samples

The enhancement of rice quality stands as a pivotal focus in crop breeding research, with spectral analysis-based non-destructive quality assessment emerging as a widely adopted tool in agriculture. A prevalent trend in this field prioritizes the assessment of effectiveness of individual spectral technologies while overlooking the influence of sample type on spectral quality testing outcomes. Thus, the present study employed Microscopic Hyperspectral Imaging, Raman, and Laser-Induced Breakdown Spectroscopy (LIBS) to acquire spectral data from paddy rice, brown rice, polished rice, and rice flour. The data were then modeled and analyzed with respect to the amylopectin and protein contents of the rice samples via regression methods. Correlation analysis revealed varying degrees of correlation, both positive and negative, among the three spectral techniques and the analytes of interest. LIBS and Raman spectroscopy demonstrated stronger correlations with the analytes compared to microscopic hyperspectral imaging. Based on the selected correlation variables, feature screening and regression modeling were conducted. The modeling results indicated that microscopic hyperspectral data modeling yielded the lowest coefficient of determination of R² = 0.2, followed by Raman data modeling result was higher than it, which was about 0.5. The modeling effect of polished rice is the best. LIBS data modeling performed best, with a coefficient of determination of 0.6. The influence of different sample types on the modeling results was less than that of Raman spectroscopy, and modeling results of grains were better. The feature matching analysis of Raman and libs spectroscopy techniques showed that there were spectral variables that could match amylopectin and protein in the features obtained by multiple modeling statistics, but some modeling variables failed to match. LIBS matched more variables than Raman. These findings provide valuable insights into the application effectiveness of different spectral techniques in detecting rice contents across diverse sample types.

High-resolution mass spectrometry-based suspect and nontarget screening of natural toxins in foodstuffs and risk assessment of dietary exposure

Daily dietary intake inevitably exposes individuals to various natural toxins, which may pose potential health threats. Focusing only on specific toxins could underestimate dietary risks. Therefore, we have developed a suspect and nontarget method based on ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) to screen both known and unknown natural toxins in various foodstuffs. An in-house database containing 2952 natural toxins including fungal toxins, phytotoxins, animal toxins and cyanotoxins was established, facilitating suspect screening. Predicted retention time and mass spectrometry data were employed to enhance the confidence levels. Subsequently, Nontarget screening method was conducted based on molecular network analysis, annotating the edges and nodes through modified types and fragmentation characteristics. Finally, we analyzed 102 foodstuff samples and identified a total of 90 natural toxins, including mycotoxins and phytotoxins, with 65 identified by suspect screening and 25 by nontarget screening. Based on measured concentrations, the daily per capita dietary intake of total natural toxins was estimated, it was below risk doses for natural toxins with available reference values. Overall, this work established a novel method for the comprehensive identification of natural toxins in foodstuffs and emphasized the importance of dietary risk assessment for natural toxins.

Multi-pesticide residue screening, identification, and quantification analysis in various fruits and vegetables by UHPLC-Q Exactive HRMS

A general strategy for qualitative screening and quantitative analysis of 403 pesticides in various fruits and vegetables was developed using ultrahigh-performance liquid chromatography (UHPLC) in conjunction with a Thermo Q Exactive Focus high-resolution mass spectrometer, relying on an executable compound database comprised of the exacted mass of precursor ions, retention times, and fragment ions. Taking advantage of the powerful separation capacity of UHPLC, an Orbitrap analyzer with high sensitivity in full scan mode and elevated mass resolution of product ions in the MS/MS mode, eight pairs of isomers and fifty-seven groups of isobaric compounds were selectively identified. The method was then systematically assessed and validated for eight fruits and vegetables, in terms of screening detection limit (SDL), matrix effects, recovery, and precision over 400 pesticides. The results showed that the SDLs of 68.0-84.4% for the pesticides were less than or equal to 10 μg kg-1 in the representative matrices, recoveries in the range of 60-120% accounting for 48.6-84.4% of all the targets at three lower fortified levels of 5, 20, and 50 μg kg-1 with a precision of less than 20% while the range of overall average recoveries for the majority of the pesticides were from 82.4% to 105.1% in the as-selected matrices with RSDs between 3.9% and 7.7%. Using this method, screening data from a survey of pesticide residues in 68 practical samples across 32 different matrix types provides scientific data for the inspection and supervision of pesticide residue safety of fruits and vegetables.

Co-contamination and interactions of multiple mycotoxins and heavy metals in rice, maize, soybeans, and wheat flour marketed in Shanghai City

Mycotoxins and heavy metals extensively contaminate grains and grain products, posing severe health risks. This work implements validated ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and inductively coupled plasma mass spectrometry (ICP-MS) methods to quantify the concentration of 12 mycotoxins and five heavy metals in rice, maize, soybeans, and wheat flour samples marketed in Shanghai. The mixed contamination characteristics were analyzed using correlation cluster analysis and co-contamination index, and the probabilities of all cross combinations of contaminations were analyzed using a self-designed JAVA language program. The results showed that grains and grain products were frequently contaminated with both mycotoxins and heavy metals, mostly with deoxynivalenol (DON), 3-acetyl-deoxynivalenol (3-ADON), 15-acetyl-deoxynivalenol (15-ADON), ochratoxin A (OTA), aflatoxins, fumonisin B1 (FB1), fumonisin B2 (FB2), fumonisin B3 (FB3), arsenic (As), chromium (Cr) and cadmium (Cd). All the samples (100 %) were contaminated with two or more contaminants, and 77.3 % of the samples were co-contaminated with more than four contaminants. In cereals and cereal products, the following combinations were closely associated: (FB3 +3-ADON), (FB1 +As), (FB1 +FB2), (DON+FB1), (DON+Cd), (As+Cd), (DON+Cd+As), (FB1 +FB2 +As), and (DON+3-ADON+15-ADON). The results indicated that mycotoxins and heavy metals frequently co-occurred in Shanghai grains and grain products, and they provided primary data for safety assessments, early warnings, and regulatory measures on these contaminants to protect public health.

Ultrasensitive Electrochemiluminescence Biosensing Platform Based on Polymer Dots with Aggregation-Induced Emission for Dual-Biotoxin Assay

Multitarget assay has always been a hot topic in electrochemiluminescence (ECL) methods. Herein, a "on-off-on" ECL aptasensor was developed for the ultrasensitive and sequential detection of possible biological warfare agents, deoxynivalenol (DON) and abrin (ABR). As a luminophore, polymer dots (Pdots) with aggregation-induced emission exhibit high ECL efficiency in the aptasensor, i.e., the signal "on" state. The DON assays mainly depend on ECL quenching due to the efficient quenching effect between ferrocene-H2-ferrocene (Fc-H2-Fc) and Pdots, i.e., the signal "off" state. When the aptasensor is incubated with the oligonucleotide sequence S2 to replace Fc-H2-Fc, obvious ECL recovery occurs, i.e., the signal "on" state, which can be used to sequentially detect ABR. The limit of detection (LOD) for DON is 0.73 fg·mL-1 in the range of 5.0 to 50 ng·mL-1; and the LOD for ABR is ∼0.38 pg·mL-1 in the range of 1.25 pg·mL-1 to 1.25 μg·mL-1. The as-designed ECL aptasensor exhibits good stability and reproducibility, high specificity, and favorable practicality. Therefore, this work provides a new approach for assays of DON and ABR in food safety and can be used as a model to design an ultrasensitive ECL biosensor for multitarget detection.

What Is Fusarium Head Blight (FHB) Resistance and What Are Its Food Safety Risks in Wheat? Problems and Solutions-A Review

The term "Fusarium Head Blight" (FHB) resistance supposedly covers common resistances to different Fusarium spp. without any generally accepted evidence. For food safety, all should be considered with their toxins, except for deoxynivalenol (DON). Disease index (DI), scabby kernels (FDK), and DON steadily result from FHB, and even the genetic regulation of Fusarium spp. may differ; therefore, multitoxin contamination is common. The resistance types of FHB form a rather complex syndrome that has been the subject of debate for decades. It seems that resistance types are not independent variables but rather a series of components that follow disease and epidemic development; their genetic regulation may differ. Spraying inoculation (Type 1 resistance) includes the phase where spores land on palea and lemma and spread to the ovarium and also includes the spread-inhibiting resistance factor; therefore, it provides the overall resistance that is needed. A significant part of Type 1-resistant QTLs could, therefore, be Type 2, requiring the retesting of the QTLs; this is, at least, the case for the most effective ones. The updated resistance components are as follows: Component 1 is overall resistance, as discussed above; Component 2 includes spreading from the ovarium through the head, which is a part of Component 1; Component 3 includes factors from grain development to ripening (FDK); Component 4 includes factors influencing DON contamination, decrease, overproduction, and relative toxin resistance; and for Component 5, the tolerance has a low significance without new results. Independent QTLs with different functions can be identified for one or more traits. Resistance to different Fusarium spp. seems to be connected; it is species non-specific, but further research is necessary. Their toxin relations are unknown. DI, FDK, and DON should be checked as they serve as the basic data for the risk analysis of cultivars. A better understanding of the multitoxin risk is needed regarding resistance to the main Fusarium spp.; therefore, an updated testing methodology is suggested. This will provide more precise data for research, genetics, and variety registration. In winter and spring wheat, the existing resistance level is very high, close to Sumai 3, and provides much greater food safety combined with sophisticated fungicide preventive control and other practices in commercial production.

Suspect and nontarget screening of mycotoxins and their modified forms in wheat products based on ultrahigh-performance liquid chromatography-high resolution mass spectrometry

Various forms of mycotoxins commonly exist in food and pose a significant risk to human health. Here a comprehensive suspect and nontarget screening strategy for both parent and modified mycotoxins was developed using ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLCHRMS). We constructed an in-house MS/MS database containing 82 mycotoxins in 8 categories. Then fragmentation characteristics of different classes of mycotoxins were rapidly extracted by a Python program "Fragmentation pattern screener (FPScreener)" and nontarget screening rules were determined by analyzing the frequencies and average intensities of fragmentation characteristics. Using the suspect and nontarget screening strategy, we successfully identified six parent mycotoxins and eight modified mycotoxins with different confidence levels in contaminated wheat and flour samples. This strategy enables screening of unknown parents and modified mycotoxins in food matrices with corresponding fragmentation characteristics.

Dual-Target Electrochemical Sensor Based on 3D MoS2-rGO and Aptamer Functionalized Probes for Simultaneous Detection of Mycotoxins

A dual-target aptamer functionalized probes (DTAFP) was applied for the detection of aflatoxin B1 (AFB1) and zearalenone (ZEN) simultaneously, which has not been reported. Meanwhile, two functional materials for signal amplification of the DTAFP were synthesized: 1) a three-dimensional molybdenum disulfide-reduced graphene oxide (MoS₂-rGO) as a favorable loading interface; 2) a double-probes gold nanoparticles (AuNPs) modified by Thionin (Thi) and 6-(Ferrocenyl) hexanethiol (FC6S) as distinguishable and non-interfering signals. Mycotoxins on the electrode surface release into solution under the function of the DTAFP, leading a reduction of the differential peak impulse in signal response. Under the optimum conditions, the aptasensor exhibited a detection range of 1.0 pg mL⁻¹–100 ng mL⁻¹ for AFB1 and ZEN, with no observable cross reactivity. In addition, the aptasensor performed excellent stability, reproducibility, specificity, and favorable recovery in the detection of edible oil. This work demonstrated a novel method for the construction of a simple, rapid, and sensitive aptasensor in the detection of multiple mycotoxins simultaneously.