Bayer Crop Science, Saint Louis, MO, USA.
Metabolomics. 2020 Oct 9;16(10):111. doi: 10.1007/s11306-020-01733-8.
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.
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.
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.
对转基因(GM)作物的食品和饲料进行安全性评估,包括比较关键特性,如作物成分、农艺表型以及动物喂养研究中的观察结果,与具有安全食用历史的传统对照品种进行比较,这些品种通常包括近等基因品种。GM 作物的比较成分分析是基于针对每种作物的关键食品和饲料营养成分和抗营养成分的靶向、验证、定量分析方法,这些方法是由经济合作与发展组织(OECD)确定的。随着非靶向代谢组学方法技术的发展,有人提议将其用于补充或替代 GM 作物监管风险评估中的靶向成分分析方法,以增加分析代谢物的数量。
审查了将非靶向代谢组学分析纳入 GM 作物比较安全性评估的技术机会、挑战和策略。过去八年发表的 GM 和常规作物代谢组学研究的结果提供了背景,使人们能够讨论代谢组学是否可以在 25 年以上全球范围内使用的经食品法典定义的实践的基础上,实质性地改进对 GM 作物食品和饲料的风险评估。
迄今为止发表的研究表明,环境和遗传因素会影响植物代谢组学图谱。相比之下,用于制造 GM 作物的植物生物技术过程几乎没有影响,除非插入的 GM 特性旨在改变食品或饲料成分。GM 作物列表中由特定作物 OECD 共识文件定义的关键分析物的定量、验证成分方法为 GM 作物食品和饲料的营养价值和安全性提供了充分的信息。非靶向代谢物谱分析尚未提供比已经严格的经食品法典定义的定量比较评估更能为 GM 作物的安全性评估提供信息的数据。此外,技术挑战限制了非靶向代谢组学在监管方面的实施:没有单一的提取方法或分析技术可以捕获完整的植物代谢组;大量代谢物特征是未知的,需要进一步研究以了解这些未知物的差异是否会影响食品/饲料安全;需要标准化方法以提供随时间和实验室变化的可重复数据。