在非目标分析中大规模生成基于in silico的光谱库以注释暗化学空间特征
Emil Egede Frøkjær1, Martin Hansen2
1Environmental Forensics and Metabolomics Laboratory, Department of Environmental and Resource Engineering, Technical University of Denmark, Bygningstorvet, Building 115, Kongens Lyngby, 2800, Hovedstaden, Denmark. emefro@dtu.dk.
这项研究引入了一个开放式的光谱库,用于在环境和食品安全分析中识别未知的化学物质. 这种资源有助于在地下水样本中发现以前未被检测到的污染物.
科学领域:
- 环境化学
- 分析化学
- 代谢学
背景情况:
- 环境,曝光学,食品安全和法医调查经常发现未知的分子特征.
- 阐明这些"暗"特征对于风险评估和合规性至关重要.
研究的目的:
- 开发和展示一个用于化学识别的开放式碎光谱库.
- 支持3级注释以阐明未知的分子特征.
- 在环境样本中发现新污染物.
主要方法:
- 在使用LC-电喷射-HRMS/MS的光谱库中产生大规模 (120,514种化学物质).
- 使用诺曼嫌疑人名单交换的化学数据.
- 应用后续的非目标选分析.
主要成果:
- 在地下水中发现了几种以前未报告的异生菌和污染物转化产物.
- 具体的例子包括六乙,六胺代谢物和三硫的转化产物,酸,三酸盐和酸.
- 在非定位的工作流程中发现这些化合物.
结论:
- 在中开发的光谱库是识别复杂矩阵中未知的化学物质的宝贵工具.
- 这种资源显著提高了环境监测和安全调查的能力.
- 图书馆是免费的,促进开放的科学和更广泛的研究应用.
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