林晓惠

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:计算机科学与技术学院

电子邮箱:datas@dlut.edu.cn

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Stable lsotope-Assisted Lipidomics Combined with Nontargeted lsotopomer Filtering, a Tool to Unravel the Complex Dynamics of Lipid Metabolism

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论文类型:期刊论文

发表时间:2013-05-07

发表刊物:ANALYTICAL CHEMISTRY

收录刊物:SCIE、EI、Scopus

卷号:85

期号:9

页面范围:4651-4657

ISSN号:0003-2700

摘要:Investigations of complex metabolic mechanisms and networks have become a focus of research in the postgenomic area, thereby creating an increasing demand for sophisticated analytical approaches. One such tool is lipidomics analysis that provides, a detailed picture of the lipid composition of a system at a given time Introducing stable isotopes into the studied system can additionally provide information on the synthesis, transformation and degradation of individual lipid species. However, capturing the entire dynamics of lipid networks is still a challenge. We developed and evaluated a novel strategy for the in-depth analysis of the dynamics of lipid metabolism with the capacity for high molecular specificity and network coverage. The general workflow consists of stable isotope-labeling experiments, ultrahigh-performance liquid chromatography (UHPLC)/high-resolution Orbitrap-mass spectrometry (MS) lipid profiling and data processing by a software tool for global isotopomer filtering and matching. As a proof of concept, this approach was applied to the network-wide mapping of dynamic lipid metabolism in primary human skeletal muscle cells cultured for 4, 12, and 24 h with [U-C-13]-palmitate. In the myocellular lipid extracts, 692 isotopomers were detected that could be assigned to 203 labeled lipid species spanning 12 lipid (sub)classes. Interestingly, some lipid classes showed high turnover rates but stable total amounts while the amount of others increased in the course of palmitate treatment. The novel strategy presented here has the potential to open new detailed insights into the dynamics of lipid metabolism that may lead to a better understanding of physiological mechanisms and metabolic perturbations.