基于化学衍生化的质谱技术在脂质分析中的研究进展  

Research Progress on Mass Spectrometry Techniques Based on Chemical Derivatization for Lipid Analysis

在线阅读下载全文

作  者:黄龙会 石幸玉 谢海洲 周婷 HUANG Long-hui;SHI Xing-yu;XIE Hai-zhou;ZHOU Ting(School of Biology and Biological Engineering,South China University of Technology,Guangzhou 510006,China)

机构地区:[1]华南理工大学生物科学与工程学院,广东广州510006

出  处:《分析测试学报》2025年第1期73-81,共9页Journal of Instrumental Analysis

基  金:国家自然科学基金项目(22374051);广州应用基础研究项目(202201010109)。

摘  要:脂质不仅是细胞膜的主要组成部分,还参与多种生命活动如能量存储、信号传导等,在生命体中发挥着重要作用。质谱以其高灵敏度、准确度和快速分析能力,在结构表征中表现出色,已成为脂质分析的核心技术。然而,由于脂质的结构多样性和高度相似性,其质谱定性、定量分析仍然面临着诸多挑战。化学衍生化技术通过对脂质进行结构修饰,可以改善脂质的离子化效率,并提高质谱检测的灵敏度与选择性,有效促进脂质的结构鉴定和定量分析。近年来,化学衍生化与质谱技术的结合策略广泛应用于脂质分析。该文综述了近十年来基于化学衍生化的质谱技术在解析脂质精确结构、提高检测灵敏度和定量准确性,以及结合新型质谱应用中的研究进展。Lipids are essential not only as major components of cell membranes but also in various bi⁃ological processes,such as energy storage and signal transduction.Due to its high sensitivity,accu⁃racy,and rapid analytical capabilities,mass spectrometry(MS)has become a core technology for lipid analysis,particularly in structural characterization.However,the structural diversity and high similarity of lipids present significant challenges for their qualitative and quantitative analysis using MS.Chemical derivatization techniques,by modifying lipid structures,can enhance ionization effi⁃ciency and improve the sensitivity and selectivity of MS detection,thus facilitating effective lipid structure identification and quantification.In recent years,the combination of chemical derivatiza⁃tion and MS has been widely applied in lipid analysis.This review summarizes the research progress of MS techniques based on chemical derivatization in resolving the structural characterization of lip⁃ids,improving detection sensitivity and quantitative accuracy,and coupling with advanced mass spectrometry over the last decade.

关 键 词:脂质 化学衍生化 质谱 结构表征 

分 类 号:O657.6[理学—分析化学] Q26[理学—化学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象