Proteomics and Metabolomics Facility, Nebraska Center for Biotechnology, University of Nebraska, Lincoln, NE 68588, USA.
Emerg Top Life Sci. 2021 May 21;5(2):189-201. doi: 10.1042/ETLS20200271.
Untargeted metabolomics enables the identification of key changes to standard pathways, but also aids in revealing other important and possibly novel metabolites or pathways for further analysis. Much progress has been made in this field over the past decade and yet plant metabolomics seems to still be an emerging approach because of the high complexity of plant metabolites and the number one challenge of untargeted metabolomics, metabolite identification. This final and critical stage remains the focus of current research. The intention of this review is to give a brief current state of LC-MS based untargeted metabolomics approaches for plant specific samples and to review the emerging solutions in mass spectrometer hardware and computational tools that can help predict a compound's molecular structure to improve the identification rate.
非靶向代谢组学能够识别标准途径的关键变化,同时还有助于揭示其他重要且可能新颖的代谢物或途径,以供进一步分析。在过去的十年中,该领域取得了很大的进展,但由于植物代谢物的高度复杂性和非靶向代谢组学的首要挑战,即代谢物鉴定,植物代谢组学似乎仍然是一种新兴的方法。最后和关键的阶段仍然是当前研究的重点。本文综述的目的是简要介绍基于 LC-MS 的针对植物特异性样品的非靶向代谢组学方法,并综述质谱仪硬件和计算工具方面的新兴解决方案,这些方案有助于预测化合物的分子结构,从而提高鉴定率。