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.

BACKGROUND: Herbicide‐resistant weeds pose a challenge to agriculture and food production. New herbicide tolerance traits in crops will provide farmers with more options to effectively manage weeds. Mesotrione, a selective pre‐ and post‐emergent triketone herbicide used in corn production, controls broadleaf and some annual grass weeds via hydroxyphenylpyruvate dioxygenase (HPPD) inhibition. Recently, the rice HIS1 gene, responsible for native tolerance to the selective triketone herbicide benzobicyclon, was identified. Expression of HIS1 also confers a modest level of mesotrione resistance in rice. Here we report the use of the HIS1 gene to develop a mesotrione tolerance trait in soybean.RESULTS: Conventional soybean is highly sensitive to mesotrione. Ectopic expression of a codon‐optimized version of the rice HIS1 gene (TDO) in soybean confers a commercial level of mesotrione tolerance. In TDO transgenic soybean plants, mesotrione is rapidly and locally oxidized into noninhibitory metabolites in leaf tissues directly exposed to the herbicide. These metabolites are further converted into compounds similar to known classes of plant secondary metabolites. This rapid metabolism prevents movement of mesotrione from treated leaves into vulnerable emerging leaves. Minimizing the accumulation of the herbicide in vulnerable emerging leaves protects the function of HPPD and carotenoid biosynthesis more generally while providing tolerance to mesotrione.CONCLUSIONS: Mesotrione has a favorable environmental and toxicological profile. The TDO‐mediated soybean mesotrione tolerance trait described here provides farmers with a new option to effectively manage difficult‐to‐control weeds using familiar herbicide chemistry. This trait can also be adapted to other mesotrione‐sensitive crops (e.g. cotton) for effective weed management. © 2022 Bayer Crop Science. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Solid-phase microextraction (SPME) was coupled to gas chromatography mass spectrometry (GC-MS) and a method optimized to quantitatively and qualitatively measure a large array of volatile metabolites in alfalfa glandular trichomes isolated from stems, trichome-free stems, and leaves as part of a non-targeted metabolomics approach. Major SPME extraction parameters optimized included SPME fiber composition, extraction temperature, and extraction time. The optimized SPME method provided the most chemically diverse coverage of alfalfa volatile and semi-volatile metabolites using a DVB/CAR/PDMS fiber, extraction temperature of 60 °C, and an extraction time of 20 min. Alfalfa SPME-GC-MS profiles were processed using automated peak deconvolution and identification (AMDIS) and quantitative data extraction software (MET-IDEA). A total of 87 trichome, 59 stem, and 99 leaf volatile metabolites were detected after background subtraction which removed contaminants present in ambient air and associated with the fibers and NaOH/EDTA buffer solution containing CaCl₂. Thirty-seven volatile metabolites were detected in all samples, while 15 volatile metabolites were uniquely detected only in glandular trichomes, 9 only in stems, and 33 specifically in leaves as tissue specific volatile metabolites. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) of glandular trichomes, stems, and leaves showed that the volatile metabolic profiles obtained from the optimized SPME-GC-MS method clearly differentiated the three tissues (glandular trichomes, stems, and leaves), and the biochemical basis for this differentiation is discussed. Although optimized using plant tissues, the method can be applied to other types of samples including fruits and other foods.

Glutamate decarboxylase (GAD; EC 4.1.1.15) catalyzes the irreversible decarboxylation of glutamate to produce γ-aminobutyric acid (GABA); a ubiquitous non-protein amino acid involved in the regulation of several aspects of plant metabolism and physiology. To study the function of GAD and GABA in maize, we have; 1) introduced native and deregulated forms of AtGAD1 into maize with the intent of increasing the synthesis of GABA and 2) introduced constructs into maize designed to suppress the activity of several GABA shunt, GABA transport and GABA pathway genes. Maize plants expressing the deregulated AtGAD1 exhibit a severe chlorosis and retarded growth phenotype and have high levels of GABA, and Ca⁺⁺/CaM-independent GAD activity. Plants expressing the suppression constructs for GABA biosynthetic and transport pathway genes had no observable phenotype whereas a knockout of GABA catabolic pathway genes led to growth and developmental defects under standard growth conditions. The implications of this study to our understanding of the action and function of GABA and GAD in crops are discussed.