Rychlik Michael, Schmitt-Kopplin Philippe
Analytical Food Chemistry, Technical University of Munich, Freising, Germany.
Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Coopers Plains, QLD, Australia.
Front Nutr. 2020 Feb 28;7:9. doi: 10.3389/fnut.2020.00009. eCollection 2020.
Predictions about the future knowledge of the "complete" food metabolome may be assayed based on the laws of Moore and Kurzweil, who foresee a technological development on exponential behavior. The application of these laws allows us to extrapolate and predict roughly when each single metabolite in foods could be (1) known, (2) detectable, and (3) identifiable. To avoid huge additional uncertainties, we restrict the range of metabolites to those in unprocessed foods. From current metabolite databases and their coverage over time, the conservative number of all considered food metabolites can be estimated to be 500,000, predicting them being known by around 2025. Assuming these laws and extrapolating the current developments in chromatography and mass spectrometry technology, the year 2032 can be estimated, when single molecule detection will be possible in "routine" mass spectrometry. A possible forecast for the identification of all food metabolites, however, is much more difficult and estimated at the earliest in 2041 as the year when this may be achieved. However, the real prediction uncertainty is extreme and is discussed in the essay presented here.
关于“完整”食物代谢组未来认知情况的预测,可以基于摩尔定律和库兹韦尔定律进行分析,他们预见了呈指数式发展的技术进步。应用这些定律能让我们推断并大致预测出食物中的每一种单一代谢物何时会(1)被知晓、(2)可检测到以及(3)可被识别。为避免出现巨大的额外不确定性,我们将代谢物范围限定为未加工食物中的代谢物。根据当前的代谢物数据库及其随时间的覆盖范围,所有被考虑的食物代谢物保守估计数量为50万种,预计到2025年左右它们将被知晓。假设这些定律并推断色谱和质谱技术的当前发展情况,预计到2032年,在“常规”质谱分析中就能够实现单分子检测。然而,对所有食物代谢物进行识别的可能预测则困难得多,最早估计要到2041年才可能实现。不过,实际的预测不确定性极大,本文对此进行了讨论。