多实验室非定向质谱仪代谢学合作,以识别瓶并全面说明单一数据集
Joelle Houriet1, Preston K Manwill1, Armando Alcázar Magaña2
1Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, North Carolina 27402, United States.
Analytical chemistry
|July 22, 2025
概括
准确注释非目标质谱代谢学数据是具有挑战性的. 本研究强调了离子物种分配和特征冗余的问题,强调了需要改进分析工具和策略的必要性.
科学领域:
- 代谢学 代谢学 代谢学
- 分析化学 分析化学
- 生物信息学是一种生物信息学.
背景情况:
- 代谢学使我们能够研究生物系统中的小分子.
- 对质谱数据的准确注释对于识别代谢物至关重要.
- 非定位代谢学旨在检测和识别广泛的代谢物.
研究的目的:
- 确定在注释非定向质谱代谢学数据集中的挑战.
- 提出克服注释困难的策略.
- 在不同的专家团队中评估代谢物注释的可复制性和准确性.
主要方法:
- 在Orbitrap和Q-ToF平台上使用液体染色学质谱法 (LC-MS) 分析灰 (Withania somnifera) 提取物.
- 在正离子模式下进行数据依赖采集 (DDA).
- 12个数据集的注释由十个专家的代谢组组.
- 交叉检查注释,以建立一个共识清单142假定分析.
主要成果:
- 在专家团队 (24-57%的共识列表) 中分析报告的显著变化.
- 在MS光谱中正确分配离子物种 (集群,碎片) 成为一个主要的瓶.
- 源内冗余经常被误认为是独立分析,导致注释错误和过度估计样本复杂性.
- 在142个共识分析分析中,只有13个被证实与标准相比.
结论:
- 目前在非目标代谢学中的注释策略面临着重大挑战,特别是在光谱解释和冗余处理方面.
- 需要改进的计算工具和标准化的方法来进行特征识别和分组.
- 对于查询光谱和分类学数据库的增强方法是必要的,以提高假定分析物结构分配的准确性.
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