使用数据依赖和数据独立的混合采集来实现基于快速液体染色学的非定位脂组学
Kanako Tokiyoshi1, Yuki Matsuzawa1, Mikiko Takahashi2
1Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei-shi, Tokyo 184-8588, Japan.
Analytical chemistry
|January 11, 2024
概括
这项研究引入了一种针对非向性脂管学的新方法,结合了数据依赖性获取 (DDA) 和全理论质谱数据独立获取 (SWATH-DIA) 的顺序窗口获取,以便在大型研究中更快,更准确地识别脂质.
科学领域:
- 生物化学和分析化学的研究.
- 质谱测量质量谱测量
- 利皮多米克 (Lipidomics) 是一种消化剂.
背景情况:
- 非向性脂质组学对于大型队列研究至关重要,但快速液体染色学 (LC) 梯度会减少脂质注释率,因为MS/MS的光谱覆盖率较低.
- 快速LC中狭窄的峰值宽度阻碍了全面的脂质分析.
研究的目的:
- 开发一个系统的程序,以实现高脂质注释率在快速LC基于非向脂质组学.
- 整合数据依赖获取 (DDA) 和顺序窗口获取全理论质谱数据独立获取 (SWATH-DIA) 以改进脂质识别.
主要方法:
- 使用MS-DIAL程序开发了一个新的工作流程,集成DDA和SWATH-DIA技术.
- 用可变SWATH-DIA方法用于质量控制 (QC) 样本,以纠正MS信号漂移.
- 使用DDA分析生物样本,以最大限度地阐明脂质的结构.
主要成果:
- 与快速LC-DDA-MS相比,DDA和SWATH-DIA的综合战略实现了注释覆盖面的1.7倍增长.
- 该方法提供了95.3%的脂质覆盖率,相当于25分钟的LC梯度,使用8.6分钟的LC梯度.
- 在大规模和小规模实验中展示了全面的脂质组概况.
结论:
- 分析条件和信息学工具的协调改进使得基于快速LC的非定向脂质组学能够进行全面的脂质组分析.
- 这种方法显著提高了临床应用和基本生物研究的脂质识别效率.
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