代谢组学分析绿色指标。

IF 3.3 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Ren-Qi Wang, Yun Wang, Juan-Na Song, Huai-Dong Yu, Xi-Zhi Niu, Elize Smit
{"title":"代谢组学分析绿色指标。","authors":"Ren-Qi Wang, Yun Wang, Juan-Na Song, Huai-Dong Yu, Xi-Zhi Niu, Elize Smit","doi":"10.1007/s11306-025-02323-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Aim of review: </strong>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.</p><p><strong>Key scientific concepts of review: </strong>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.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"121"},"PeriodicalIF":3.3000,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytical greenness metrics for metabolomics.\",\"authors\":\"Ren-Qi Wang, Yun Wang, Juan-Na Song, Huai-Dong Yu, Xi-Zhi Niu, Elize Smit\",\"doi\":\"10.1007/s11306-025-02323-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Aim of review: </strong>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.</p><p><strong>Key scientific concepts of review: </strong>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.</p>\",\"PeriodicalId\":18506,\"journal\":{\"name\":\"Metabolomics\",\"volume\":\"21 5\",\"pages\":\"121\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metabolomics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11306-025-02323-2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11306-025-02323-2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

摘要

背景:代谢组学正在迅速发展,解决了在极其复杂的样品中代谢物的定性和定量分析化学方面的挑战。靶向代谢组学涉及目标化合物的提取和分析,通常以极低的浓度存在,而非靶向代谢组学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过量废物,绿色指标对于考虑可持续发展至关重要。综述的目的:确定分析绿色计算器(AGREE)在评价代谢组学方法的分析绿色度中的适用性。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,并对每个程序的详细绿色参数进行了合理估计。回顾的关键科学概念:计算的AGREE指标明确显示了当前研究中绿色的主要弱点,并提供了代谢组学可持续实践的指导方针。结果表明,离线样品制备和缺乏自动化和小型化是必须解决的关键领域,以使代谢组学更具可持续性。应考虑的重要方面包括样品制备程序的复杂性、有毒试剂和衍生试剂的使用、产生的废物量和样品吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytical greenness metrics for metabolomics.

Background: 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.

Aim of review: 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.

Key scientific concepts of review: 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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Metabolomics
Metabolomics 医学-内分泌学与代谢
CiteScore
6.60
自引率
2.80%
发文量
84
审稿时长
2 months
期刊介绍: Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to: metabolomic applications within man, including pre-clinical and clinical pharmacometabolomics for precision medicine metabolic profiling and fingerprinting metabolite target analysis metabolomic applications within animals, plants and microbes transcriptomics and proteomics in systems biology Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信