The Impact of Bt Corn on Aflatoxin-Related Insurance Claims in the United States

MicroRNA (miRNA) profiling of maize genotypes with differential response to Aspergillus flavus implies zma-miR156-squamosa promoter binding protein (SBP) and zma-miR398/zma-miR394-F -box combinations involved in resistance mechanisms

Maize (Zea mays), a major food crop worldwide, is susceptible to infection by the saprophytic fungus Aspergillus flavus that can produce the carcinogenic metabolite aflatoxin (AF) especially under climate change induced abiotic stressors that favor mold growth. Several studies have used "-omics" approaches to identify genetic elements with potential roles in AF resistance, but there is a lack of research identifying the involvement of small RNAs such as microRNAs (miRNAs) in maize-A. flavus interaction. In this study, we compared the miRNA profiles of three maize lines (resistant TZAR102, moderately resistant MI82, and susceptible Va35) at 8 h, 3 d, and 7 d after A. flavus infection to investigate possible regulatory antifungal role of miRNAs. A total of 316 miRNAs (275 known and 41 putative novel) belonging to 115 miRNA families were identified in response to the fungal infection across all three maize lines. Eighty-two unique miRNAs were significantly differentially expressed with 39 miRNAs exhibiting temporal differential regulation irrespective of the maize genotype, which targeted 544 genes (mRNAs) involved in diverse molecular functions. The two most notable biological processes involved in plant immunity, namely cellular responses to oxidative stress (GO:00345990) and reactive oxygen species (GO:0034614) were significantly enriched in the resistant line TZAR102. Coexpression network analysis identified 34 hubs of miRNA-mRNA pairs where nine hubs had a node in the module connected to their target gene with potentially important roles in resistance/susceptible response of maize to A. flavus. The miRNA hubs in resistance modules (TZAR102 and MI82) were mostly connected to transcription factors and protein kinases. Specifically, the module of miRNA zma-miR156b-nb - squamosa promoter binding protein (SBP), zma-miR398a-3p - SKIP5, and zma-miR394a-5p - F-box protein 6 combinations in the resistance-associated modules were considered important candidates for future functional studies.

Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning

Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices.

Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois - First USA case study

Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict mycotoxin contamination of corn in Illinois, a major corn producing state in the USA. Historical monthly meteorological data from a 14-year period combined with corresponding aflatoxin and fumonisin contamination data from the State of Illinois were used to engineer input features that link weather, fungal growth, and aflatoxin production in combination with gradient boosting (GBM) and bayesian network (BN) modeling. The GBM and BN models developed can predict mycotoxin contamination with overall 94% accuracy. Analyses for aflatoxin and fumonisin with GBM showed that meteorological and satellite-acquired vegetative index data during March significantly influenced grain contamination at the end of the corn growing season. Prediction of high aflatoxin contamination levels was linked to high aflatoxin risk index in March/June/July, high vegetative index in March and low vegetative index in July. Correspondingly, high levels of fumonisin contamination were linked to high precipitation levels in February/March/September and high vegetative index in March. During corn flowering time in June, higher temperatures range increased prediction of high levels of fumonisin contamination, while high aflatoxin contamination levels were linked to high aflatoxin risk index. Meteorological events prior to corn planting in the field have high influence on predicting aflatoxin and fumonisin contamination levels at the end of the year. These early-year events detected by the models can directly assist farmers and stakeholders to make informed decisions to prevent mycotoxin contamination of Illinois grown corn.

Characterization of the Aspergillus flavus Population from Highly Aflatoxin-Contaminated Corn in the United States

Aflatoxin contamination of corn is a major threat to the safe food and feed. The United States Federal Grain Inspection Service (FGIS) monitors commercial grain shipments for the presence of aflatoxin. A total of 146 Aspergillus flavus were isolated from 29 highly contaminated grain samples to characterize the visual phenotypes, aflatoxin-producing potential, and genotypes to explore the etiological cause of high aflatoxin contamination of US corn. Five of the isolates had reduced sensitivity (43-49% resistant) to the fungicide azoxystrobin, with the remainder all being over 50% resistant to azoxystrobin at the discriminating dose of 2.5 µg/mL. Only six isolates of the highly aflatoxigenic S morphotype were found, and 48 isolates were non-aflatoxigenic. Analysis of the mating type locus revealed 45% MAT 1-1 and 55% MAT 1-2. The A. flavus population originating from the highly aflatoxin contaminated grain samples was compared to a randomly selected subset of isolates originating from commercial corn samples with typical levels of aflatoxin contamination (average < 50 ppb). Use of simple sequence repeat (SSR) genotyping followed by principal component analysis (PCoA) revealed a similar pattern of genotypic distribution in the two populations, but greater diversity in the FGIS-derived population. The noticeable difference between the two populations was that genotypes identical to strain NRRL 21882, the active component of the aflatoxin biocontrol product Afla-Guard™, were ten times more common in the commercial corn population of A. flavus compared to the population from the high-aflatoxin corn samples. The other similarities between the two populations suggest that high aflatoxin concentrations in corn grain are generally the result of infection with common A. flavus genotypes.

Early Warning of Resistance to Bt Toxin Vip3Aa in Helicoverpa zea

Evolution of resistance by pests can reduce the benefits of crops genetically engineered to produce insecticidal proteins from Bacillus thuringiensis (Bt). Because of the widespread resistance of Helicoverpa zea to crystalline (Cry) Bt toxins in the United States, the vegetative insecticidal protein Vip3Aa is the only Bt toxin produced by Bt corn and cotton that remains effective against some populations of this polyphagous lepidopteran pest. Here we evaluated H. zea resistance to Vip3Aa using diet bioassays to test 42,218 larvae from three lab strains and 71 strains derived from the field during 2016 to 2020 in Arkansas, Louisiana, Mississippi, Tennessee, and Texas. Relative to the least susceptible of the three lab strains tested (BZ), susceptibility to Vip3Aa of the field-derived strains decreased significantly from 2016 to 2020. Relative to another lab strain (TM), 7 of 16 strains derived from the field in 2019 were significantly resistant to Vip3Aa, with up to 13-fold resistance. Susceptibility to Vip3Aa was significantly lower for strains derived from Vip3Aa plants than non-Vip3Aa plants, providing direct evidence of resistance evolving in response to selection by Vip3Aa plants in the field. Together with previously reported data, the results here convey an early warning of field-evolved resistance to Vip3Aa in H. zea that supports calls for urgent action to preserve the efficacy of this toxin.

Managing resistance evolution to transgenic Bt maize in corn borers in Spain

Since 1998, genetically engineered Bt maize varieties expressing the insecticidal Cry1Ab protein (i.e. event MON 810) have been grown in the European Union (EU), mainly in Spain. These varieties confer resistance against the European and Mediterranean corn borer (ECB and MCB), which are the major lepidopteran maize pests in the EU, particularly in Mediterranean areas. However, widespread, repeated and exclusive use of Bt maize is anticipated to increase the risk of Cry1Ab resistance to evolve in corn borer populations. To delay resistance evolution, typically, refuges of non-Bt maize are planted near or adjacent to, or within Bt maize fields. Moreover, changes in Cry1Ab susceptibility in field populations of corn borers and unexpected damage to maize MON 810, due to corn borers, are monitored on an annual basis. After two decades of Bt maize cultivation in Spain, neither resistant corn borer populations nor farmer complaints on unexpected field damage have been reported. However, whether the resistance monitoring strategy followed in Spain, currently based on discriminating concentration bioassays, is sufficiently sensitive to timely detect early warning signs of resistance in the field remains a point of contention. Moreover, the Cry1Ab resistance allele frequency to Bt maize, which has recently been estimated in MCB populations from north-eastern Spain, might exceed that recommended for successful resistance management. To ensure Bt maize durability in Spain, it is key that adequate resistance management approaches, including monitoring of resistance and farmer compliance with refuge requirements, continue to be implemented and are incorporated in integrated pest management schemes.

Possibilities for the Biological Control of Mycotoxins in Food and Feed

Seeking useful biological agents for mycotoxin detoxification has achieved success in the last twenty years thanks to the participation of many multidisciplinary teams. We have recently witnessed discoveries in the fields of bacterial genetics (inclusive of next-generation sequencing), protein encoding, and bioinformatics that have helped to shape the latest perception of how microorganisms/mycotoxins/environmental factors intertwine and interact, so the road is opened for new breakthroughs. Analysis of literature data related to the biological control of mycotoxins indicates the ability of yeast, bacteria, fungi and enzymes to degrade or adsorb mycotoxins, which increases the safety and quality of susceptible crops, animal feed and, ultimately, food of animal origin (milk, meat and eggs) by preventing the presence of residues. Microbial detoxification (transformation and adsorption) is becoming a trustworthy strategy that leaves no or less toxic compounds and contributes to food security. This review summarizes the data and highlights the importance and prospects of these methods.

Forty Years of Food Safety Risk Assessment: A History and Analysis

Before the founding of the Society for Risk Analysis (SRA) in 1980, food safety in the United States had long been a concern, but there was a lack of systematic methods to assess food-related risks. In 1906, the U.S. Congress passed, and President Roosevelt signed, the Pure Food and Drug Act and the Meat Inspection Act to regulate food safety at the federal level. This Act followed the publication of multiple reports of food contamination, culminating in Upton Sinclair's novel The Jungle, which highlighted food and worker abuses in the meatpacking industry. Later in the 20th century, important developments in agricultural and food technology greatly increased food production. But chemical exposures from agricultural and other practices resulted in major amendments to federal food laws, including the Delaney Clause, aimed specifically at cancer-causing chemicals. Later in the 20th century, when quantitative risk assessment methods were given greater scientific status in a seminal National Research Council report, food safety risk assessment became more systematized. Additionally, in these last 40 years, food safety research has resulted in increased understanding of a range of health effects from foodborne chemicals, and technological developments have improved U.S. food safety from farm to fork by offering new ways to manage risks. We discuss the history of food safety and the role risk analysis has played in its evolution, starting from over a century ago, but focusing on the last 40 years. While we focus on chemical risk assessment in the U.S., we also discuss microbial risk assessment and international food safety.