Can –omics inform a food safety assessment?

Constraints and Prospects of Improving Cowpea Productivity to Ensure Food, Nutritional Security and Environmental Sustainability

Providing safe and secure food for an increasing number of people globally is challenging. Coping with such a human population by merely applying the conventional agricultural production system has not proved to be agro-ecologically friendly; nor is it sustainable. Cowpea (Vigna unguiculata (L) Walp) is a multi-purpose legume. It consists of high-quality protein for human consumption, and it is rich in protein for livestock fodder. It enriches the soil in that it recycles nutrients through the fixation of nitrogen in association with nodulating bacteria. However, the productivity of this multi-functional, indigenous legume that is of great value to African smallholder farmers and the rural populace, and also to urban consumers and entrepreneurs, is limited. Because cowpea is of strategic importance in Africa, there is a need to improve on its productivity. Such endeavors in Africa are wrought with challenges that include drought, salinity, the excessive demand among farmers for synthetic chemicals, the repercussions of climate change, declining soil nutrients, microbial infestations, pest issues, and so forth. Nevertheless, giant strides have already been made and there have already been improvements in adopting sustainable and smart biotechnological approaches that are favorably influencing the production costs of cowpea and its availability. As such, the prospects for a leap in cowpea productivity in Africa and in the enhancement of its genetic gain are good. Potential and viable means for overcoming some of the above-mentioned production constraints would be to focus on the key cowpea producer nations in Africa and to encourage them to embrace biotechnological techniques in an integrated approach to enhance for sustainable productivity. This review highlights the spectrum of constraints that limit the cowpea yield, but looks ahead of the constraints and seeks a way forward to improve cowpea productivity in Africa. More importantly, this review investigates applications and insights concerning mechanisms of action for implementing eco-friendly biotechnological techniques, such as the deployment of bio inoculants, applying climate-smart agricultural (CSA) practices, agricultural conservation techniques, and multi-omics smart technology in the spheres of genomics, transcriptomics, proteomics, and metabolomics, for improving cowpea yields and productivity to achieve sustainable agro-ecosystems, and ensuring their stability.

Machine learning-enabled non-destructive paper chromogenic array detection of multiplexed viable pathogens on food

Fast and simultaneous identification of multiple viable pathogens on food is critical to public health. Here we report a pathogen identification system using a paper chromogenic array (PCA) enabled by machine learning. The PCA consists of a paper substrate impregnated with 23 chromogenic dyes and dye combinations, which undergo colour changes on exposure to volatile organic compounds emitted by pathogens of interest. These colour changes are digitized and used to train a multi-layer neural network (NN), endowing it with high-accuracy (91-95%) strain-specific pathogen identification and quantification capabilities. The trained PCA-NN system can distinguish between viable Escherichia coli, E. coli O157:H7 and other viable pathogens, and can simultaneously identify both E. coli O157:H7 and Listeria monocytogenes on fresh-cut romaine lettuce, which represents a realistic and complex environment. This approach has the potential to advance non-destructive pathogen detection and identification on food, without enrichment, culturing, incubation or other sample preparation steps.

Evaluation of the use of untargeted metabolomics in the safety assessment of genetically modified crops

BACKGROUND

The safety assessment of foods and feeds from genetically modified (GM) crops includes the comparison of key characteristics, such as crop composition, agronomic phenotype and observations from animal feeding studies compared to conventional counterpart varieties that have a history of safe consumption, often including a near isogenic variety. The comparative compositional analysis of GM crops has been based on targeted, validated, quantitative analytical methods for the key food and feed nutrients and antinutrients for each crop, as identified by Organization of Economic Co-operation and Development (OCED). As technologies for untargeted metabolomic methods have evolved, proposals have emerged for their use to complement or replace targeted compositional analytical methods in regulatory risk assessments of GM crops to increase the number of analyzed metabolites.

AIM OF REVIEW

The technical opportunities, challenges and strategies of including untargeted metabolomics analysis in the comparative safety assessment of GM crops are reviewed. The results from metabolomics studies of GM and conventional crops published over the last eight years provide context to enable the discussion of whether metabolomics can materially improve the risk assessment of food and feed from GM crops beyond that possible by the Codex-defined practices used worldwide for more than 25 years.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Published studies to date show that environmental and genetic factors affect plant metabolomics profiles. In contrast, the plant biotechnology process used to make GM crops has little, if any consequence, unless the inserted GM trait is intended to alter food or feed composition. The nutritional value and safety of food and feed from GM crops is well informed by the quantitative, validated compositional methods for list of key analytes defined by crop-specific OECD consensus documents. Untargeted metabolic profiling has yet to provide data that better informs the safety assessment of GM crops than the already rigorous Codex-defined quantitative comparative assessment. Furthermore, technical challenges limit the implementation of untargeted metabolomics for regulatory purposes: no single extraction method or analytical technique captures the complete plant metabolome; a large percentage of metabolites features are unknown, requiring additional research to understand if differences for such unknowns affect food/feed safety; and standardized methods are needed to provide reproducible data over time and laboratories.

Obligatory metabolomic profiling of gene-edited crops is risk disproportionate

It has been argued that the application of metabolomics to gene-edited crops would present value in three areas: (i) the detection of gene-edited crops; (ii) the characterization of unexpected changes that might affect safety; and (iii) building on the track record of rigorous government regulation in supporting consumer acceptance of genetically modified organisms (GMOs). Here, we offer a different perspective, relative to each of these areas: (i) metabolomics is unable to differentiate whether a mutation has resulted from gene editing or from traditional breeding techniques; (ii) it is risk-disproportionate to apply metabolomics for regulatory purposes to search for possible compositional differences within crops developed using the least likely technique to generate unexpected compositional changes; and (iii) onerous regulations for genetically engineered crops have only contributed to unwarranted public fears, and repeating this approach for gene-edited crops is unlikely to result in a different outcome. It is also suggested that article proposing the utility of specific analytical techniques to support risk assessment would benefit from the input of scientists with subject matter expertise in risk assessment.

Assessment of the potential allergenicity of genetically-engineered food crops

An extensive safety assessment process exists for genetically-engineered (GE) crops. The assessment includes an evaluation of the introduced protein as well as the crop containing the protein with the goal of demonstrating the GE crop is "as-safe-as" non-GE crops in the food supply. One of the evaluations for GE crops is to assess the expressed protein for allergenic potential. Currently, no single factor is recognized as a predictor for protein allergenicity. Therefore, a weight-of-the-evidence approach, which accounts for a variety of factors and approaches for an overall assessment of allergenic potential, is conducted. This assessment includes an evaluation of the history of exposure and safety of the gene(s) source; protein structure (e.g. amino acid sequence identity to human allergens); stability of the protein to pepsin digestion in vitro; heat stability of the protein; glycosylation status; and when appropriate, specific IgE binding studies with sera from relevant clinically allergic subjects. Since GE crops were first commercialized over 20 years ago, there is no proof that the introduced novel protein(s) in any commercialized GE food crop has caused food allergy.

Effect of Genetics, Environment, and Phenotype on the Metabolome of Maize Hybrids Using GC/MS and LC/MS

We evaluated the variability of metabolites in various maize hybrids due to the effect of environment, genotype, phenotype as well as the interaction of the first two factors. We analyzed 480 forage and the same number of grain samples from 21 genetically diverse non-GM Pioneer brand maize hybrids, including some with drought tolerance and viral resistance phenotypes, grown at eight North American locations. As complementary platforms, both GC/MS and LC/MS were utilized to detect a wide diversity of metabolites. GC/MS revealed 166 and 137 metabolites in forage and grain samples, respectively, while LC/MS captured 1341 and 635 metabolites in forage and grain samples, respectively. Univariate and multivariate analyses were utilized to investigate the response of the maize metabolome to the environment, genotype, phenotype, and their interaction. Based on combined percentages from GC/MS and LC/MS datasets, the environment affected 36% to 84% of forage metabolites, while less than 7% were affected by genotype. The environment affected 12% to 90% of grain metabolites, whereas less than 27% were affected by genotype. Less than 10% and 11% of the metabolites were affected by phenotype in forage and grain, respectively. Unsupervised PCA and HCA analyses revealed similar trends, i.e., environmental effect was much stronger than genotype or phenotype effects. On the basis of comparisons of disease tolerant and disease susceptible hybrids, neither forage nor grain samples originating from different locations showed obvious phenotype effects. Our findings demonstrate that the combination of GC/MS and LC/MS based metabolite profiling followed by broad statistical analysis is an effective approach to identify the relative impact of environmental, genetic and phenotypic effects on the forage and grain composition of maize hybrids.

The Omics Revolution in Agricultural Research

The Agrochemicals Division cosponsored the 13th International Union of Pure and Applied Chemistry International Congress of Pesticide Chemistry held as part of the 248th National Meeting and Exposition of the American Chemical Society in San Francisco, CA, USA, August 10-14, 2014. The topic of the Congress was Crop, Environment, and Public Health Protection; Technologies for a Changing World. Over 1000 delegates participated in the Congress with interactive scientific programming in nine major topic areas including the challenges and opportunities of agricultural biotechnology. Plenary speakers addressed global issues related to the Congress theme prior to the daily technical sessions. The plenary lecture addressing the challenges and opportunities that omic technologies provide agricultural research is presented here. The plenary lecture provided the diverse audience with information on a complex subject to stimulate research ideas and provide a glimpse of the impact of omics on agricultural research.

Metabolomics of genetically modified crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

Measurement of endogenous allergens in genetically modified soybeans--short communication

The measurement of endogenous allergens is required by the European Commission (EC) as part of the compositional analysis for GM products from host plants that are common causes of food allergy, such as soybean (EC Implementing Regulation No. 503/2013). In each case, the EC Implementing Regulation indicates that analysis be conducted on identified allergens as specified in the Organization of Economic Cooperation and Development (OECD) consensus documents on compositional considerations for new plant varieties. This communication discusses the methods available to measure endogenous allergens as well as the endogenous soybean allergens that should be analyzed. It is suggested herein that in conjunction with the 2012 OECD consensus document on soybean, any list of soybean allergens should be based on clinically relevant data among publicly available allergen databases and peer-reviewed scientific publications, and the ability to measure the identified allergen. Based on a detailed analysis of the scientific literature, the following key points are recommended: (1) the acceptance of serum-free, quantitative analytical method data as an alternative to traditional IgE reactivity qualitative or semi-quantitative data for evaluation of endogenous soybean allergen content; (2) eight of the 15 potential allergens listed in the OECD soybean consensus document (Gly m 3, Gly m 4, Gly m Bd28K, Gly m Bd30K, Gly m 5, Gly m 6, Gly m 8, and Kunitz trypsin inhibitor) have both appropriate supporting clinical data and sufficient sequence information to be evaluated in comparative endogenous soybean allergen studies; and (3) the remaining seven proteins (Gly m 1, Gly m 2, unknown 50kDa protein, unknown 39kDa protein, P-22-25, lipoxygenase and lectin) lack sufficient data for clear classification as confirmed allergens and/or available sequence information and should not be currently included in the measurement of endogenous soybean allergens in the compositional analysis for the EU.

Analytical method evaluation and discovery of variation within maize varieties in the context of food safety: transcript profiling and metabolomics

Profiling techniques such as microarrays, proteomics, and metabolomics are used widely to assess the overall effects of genetic background, environmental stimuli, growth stage, or transgene expression in plants. To assess the potential regulatory use of these techniques in agricultural biotechnology, we carried out microarray and metabolomic studies of 3 different tissues from 11 conventional maize varieties. We measured technical variations for both microarrays and metabolomics, compared results from individual plants and corresponding pooled samples, and documented variations detected among different varieties with individual plants or pooled samples. Both microarray and metabolomic technologies are reproducible and can be used to detect plant-to-plant and variety-to-variety differences. A pooling strategy lowered sample variations for both microarray and metabolomics while capturing variety-to-variety variation. However, unknown genomic sequences differing between maize varieties might hinder the application of microarrays. High-throughput metabolomics could be useful as a tool for the characterization of transgenic crops. However, researchers will have to take into consideration the impact on the detection and quantitation of a wide range of metabolites on experimental design as well as validation and interpretation of results.

Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics

We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

Food safety: importance of composition for assessing genetically modified cassava (Manihot esculenta Crantz)

The importance of food composition in safety assessments of genetically modified (GM) food is described for cassava ( Manihot esculenta Crantz) that naturally contains significantly high levels of cyanogenic glycoside (CG) toxicants in roots and leaves. The assessment of the safety of GM cassava would logically require comparison with a non-GM crop with a proven "history of safe use". This study investigates this statement for cassava. A non-GM comparator that qualifies would be a processed product with CG level below the approved maximum level in food and that also satisfies a "worst case" of total dietary consumption. Although acute and chronic toxicity benchmark CG values for humans have been determined, intake data are scarce. Therefore, the non-GM cassava comparator is defined on the "best available knowledge". We consider nutritional values for cassava and conclude that CG residues in food should be a priority topic for research.

Plurality of opinion, scientific discourse and pseudoscience: an in depth analysis of the Séralini et al. study claiming that Roundup™ Ready corn or the herbicide Roundup™ cause cancer in rats

A recent paper published in the journal Food and Chemical Toxicology presents the results of a long-term toxicity study related to a widely-used commercial herbicide (Roundup™) and a Roundup-tolerant genetically modified variety of maize, concluding that both the herbicide and the maize varieties are toxic. Here we discuss the many errors and inaccuracies in the published article resulting in highly misleading conclusions, whose publication in the scientific literature and in the wider media has caused damage to the credibility of science and researchers in the field. We and many others have criticized the study, and in particular the manner in which the experiments were planned, implemented, analyzed, interpreted and communicated. The study appeared to sweep aside all known benchmarks of scientific good practice and, more importantly, to ignore the minimal standards of scientific and ethical conduct in particular concerning the humane treatment of experimental animals.

Proteomic evaluation of genetically modified crops: current status and challenges

Hectares of genetically modified (GM) crops have increased exponentially since 1996, when such crops began to be commercialized. GM biotechnology, together with conventional breeding, has become the main approach to improving agronomic traits of crops. However, people are concerned about the safety of GM crops, especially GM-derived food and feed. Many efforts have been made to evaluate the unintended effects caused by the introduction of exogenous genes. "Omics" techniques have advantages over targeted analysis in evaluating such crops because of their use of high-throughput screening. Proteins are key players in gene function and are directly involved in metabolism and cellular development or have roles as toxins, antinutrients, or allergens, which are essential for human health. Thus, proteomics can be expected to become one of the most useful tools in safety assessment. This review assesses the potential of proteomics in evaluating various GM crops. We further describe the challenges in ensuring homogeneity and sensitivity in detection techniques.

Translational plant proteomics: a perspective

Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics.

Molecular profiling--a tool for addressing emerging gaps in the comparative risk assessment of GMOs

Assessing the risks of genetically modified organisms (GMOs) is required by both international agreement and domestic legislation. Many view the use of the "omics" tools for profiling classes of molecules as useful in risk assessment, but no consensus has formed on the need or value of these techniques for assessing the risks of all GMOs. In this and many other cases, experts support case-by-case use of molecular profiling techniques for risk assessment. We review the latest research on the applicability and usefulness of molecular profiling techniques for GMO risk assessment. As more and more kinds of GMOs and traits are developed, broader use of molecular profiling in a risk assessment may be required to supplement the comparative approach to risk assessment. The literature-based discussions on the use of profiling appear to have settled on two findings: 1. profiling techniques are reliable and relevant, at least no less so than other techniques used in risk assessment; and 2. although not required routinely, regulators should be aware of when they are needed. The dismissal of routine molecular profiling may be confusing to regulators who then lack guidance on when molecular profiling might be worthwhile. Molecular profiling is an important way to increase confidence in risk assessments if the profiles are properly designed to address relevant risks and are applied at the correct stage of the assessment.