在UPLC-Q-Orbitrap质谱仪上对DDA和DIA获取模式进行比较研究,使用华粉
Di Wang1, Lei Yin2, Linglong Wang3
1School of Pharmacy, Chengdu University of Traditional Chinese Medicine; diwang1992@126.com.
Journal of visualized experiments : JoVE
|October 20, 2025
概括
数据依赖获取 (DDA) 识别了更多的化合物,而数据独立获取 (DIA) 为传统中医 (TCM) 化学分析提供了更高的可信度识别和更好的可重复性.
科学领域:
- 分析化学 分析化学
- 药理学 药理学是指药理学的学科.
- 自然产品化学 自然产品化学
背景情况:
- 传统中医药 (TCM) 配方是复杂的混合物,需要先进的分析技术来进行全面的化学分析.
- 超高性能液态染色学-四极-轨道轨道高分辨率质谱学 (UPLC-Q-轨道轨道 HRMS) 是分析这些复杂样品的强大工具.
- 数据依赖采集 (DDA) 和数据独立采集 (DIA) 是两个具有明显优缺点的质谱初级采集模式.
研究的目的:
- 系统地评估和比较DDA和DIA获取模式的性能,用于TCM配方的全面化学分析.
- 评估每个获取模式对化合物识别,可重复性,光谱质量和低丰度化合物的灵敏性的影响.
- 为TCM研究提供实验证据,以指导选择适当的质谱学获取策略.
主要方法:
- 开发了优化的DDA和DIA方法,并应用于分析Huaihua粉末,一种模型TCM配方.
- DDA利用有针对性的前体离子选择和定制的碎片化,而DIA使用细分的可变窗口获取来实现公正的碎片化.
- 使用Compound Discoverer软件进行了复合物识别和数据分析,重点是定量和定性绩效指标.
主要成果:
- DDA发现的化合物的总数较多,而 DIA发现的高度可靠性识别的比例更高 (>0.8光谱匹配得分).
- 与DDA相比,DIA在代表性化合物的保留时间和峰值面积上表现出明显优异的可重复性.
- DIA成功检测到DDA无法检测的低丰度活性成分,尽管DDA提供了更清洁的MS/MS光谱.
结论:
- DDA和DIA都为复杂的TCM的化学分析提供了互补的优势.
- DIA在可复制性和检测低丰度化合物方面表现出色,而DDA则提供更高的吞吐量和更清洁的光谱.
- 整合DDA和DIA策略可以提高TCM化学表征的全面性和可靠性.
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