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对非目标代谢和环境样本分子网络的数据依赖性MS/MS获取参数的评估:专注于Q Exactive平台

Paolo Stincone¹, Abzer K Pakkir Shah¹, Robin Schmid²

¹Cluster of Excellence-Controlling Microbes to Fight Infection, University of Tübingen, Tübingen 72076, Germany.

Analytical chemistry

|August 14, 2023

概括

在Q Exactive质谱仪上优化数据依赖的采集设置对于代谢学至关重要. 自动增强控制,扫描,分辨率和动态排除显著影响环境样本中的化合物识别.

科学领域:

环境科学环境科学
分析化学是一种分析化学.
代谢学代谢学代谢学

背景情况:

非向液体色谱-并联质谱 (LC-MS/MS) 对代谢学至关重要.
数据依赖获取 (DDA) 是频谱分析的一个常见策略.
优化DDA参数对于准确的化合物检测和注释至关重要.

研究的目的:

为了评估10个DDA设置对Q Exactive质谱仪的影响.
用来自各种环境来源 (海洋,河流,土壤) 的自然有机物质来评估这些环境.
为优化DDA参数提供指导,以改善代谢学分析.

主要方法:

使用非目标LC-MS/MS进行代谢分析.
应用数据依赖采集 (DDA) 使用不同的参数设置.
使用MZmine和GNPS分析数据,用于分子网络和统计分析.
评估了光谱质量,注释率和网络指标.

主要成果:

自动增益控制,微扫描,质量解析功率和动态排除被确定为关键的DDA参数.
碰撞能量,TopN和隔离宽度显示中度影响.
峰触发,单同位素选择和同位素排除对数据质量和注释产生了很小的影响.

结论:

特定的DDA参数显著影响从环境样本中获得的代谢学数据的质量和数量.
这些发现为Q Exactive平台上的方法优化提供了实际指导.
这些见解可能可转移到其他质谱平台和样本类型,以加强代谢学研究.

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