Wang Ren-Qi, Wang Yun, Song Juan-Na, Yu Huai-Dong, Niu Xi-Zhi, Smit Elize
School of Food and Biological Engineering, Shaanxi University of Science & Technology, Xi'an, 710021, P. R. China.
Gezhu Bio Co., Ltd, Beijing, 100037, P. R. China.
Metabolomics. 2025 Aug 19;21(5):121. doi: 10.1007/s11306-025-02323-2.
Metabolomics is rapidly evolving, addressing analytical chemistry challenges in the qualification and quantitation of metabolites in extremely complex samples. Targeted metabolomics involves the extraction and analysis of target compounds, often present at extremely low concentrations, whilst untargeted metabolomics requires the use of sophisticated analytical techniques to deal with the simultaneous identification or quantitation of hundreds of compounds. Given the high energy consumption and excessive amounts of waste generated by metabolomics studies, greenness metrics are essential to account for sustainable development.
To determine the applicability of the Analytical GREEnness calculator (AGREE) in evaluating the analytical greenness of metabolomics methods. Specifically, the analytical protocols of 16 state-of-art metabolomics studies, including nine targeted and seven untargeted metabolomics studies, are fully dissected, and detailed greenness parameters for each procedure are rationally estimated.
The calculated AGREE metrics unequivocally show the main weaknesses of greenness in current research, and guidelines for sustainable practices in metabolomics are provided. The results indicate that offline sample preparation and the lack of automation and miniaturization are key areas that must be addressed to make metabolomics more sustainable. Important aspects that should be considered include the complexity of sample preparation procedures, the use of toxic reagents and derivatizing agents, the amount of waste generated, and sample throughput.
代谢组学正在迅速发展，应对在极其复杂的样品中对代谢物进行定性和定量分析时的分析化学挑战。靶向代谢组学涉及对通常以极低浓度存在的目标化合物的提取和分析，而非靶向代谢组学则需要使用复杂的分析技术来处理数百种化合物的同时鉴定或定量。鉴于代谢组学研究产生的高能耗和大量废物，绿色指标对于可持续发展至关重要。
确定分析绿色度计算器（AGREE）在评估代谢组学方法分析绿色度方面的适用性。具体而言，对16项最新代谢组学研究的分析方案进行了全面剖析，其中包括9项靶向代谢组学研究和7项非靶向代谢组学研究，并合理估算了每个程序的详细绿色度参数。
计算得出的AGREE指标明确显示了当前研究中绿色度的主要弱点，并提供了代谢组学可持续实践的指南。结果表明，离线样品制备以及缺乏自动化和小型化是使代谢组学更具可持续性必须解决的关键领域。应考虑的重要方面包括样品制备程序的复杂性、有毒试剂和衍生化试剂的使用、产生的废物量以及样品通量。
