Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata  

作　　者：Shiwen Wu Zhen Fan Youli Xiao 

机构地区：[1]CAS Key Laboratory of Synthetic Biology,CAS Center for Excellence in Molecular Plant Sciences,Institute of Plant Physiology and Ecology,Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences,Shanghai,200032,China [2]University of Chinese Academy of Sciences,Beijing,100039,China [3]CAS-JIC Centre of Excellence in Plant and Microbial Sciences,Shanghai,200032,China

出　　处：《Synthetic and Systems Biotechnology》2018年第1期44-55,共12页合成和系统生物技术（英文）

基　　金：This work was financially supported by the Science and Technology Commission of Shanghai Municipality(Grant 15JC1400402);CAS-JIC Centre of Excellence in Plant and Microbial Sciences(CEPAMS)funding,and the Strategic Priority Research Program“Molecular mechanism of Plant Growth and Development”of CAS(Grant XDPB0402).

摘　　要：Qian ceng Ta,the whole plant of Huperzia serrata,is an important landscape and medicinal herbs and contains abundant bioactive lycopodium alkaloids.Although the structures of more than 100 lycopodium alkaloids in Huperzia serrata have been isolated and identified,the content and distribution of these alkaloids in different tissues are still unclear.In current study,an ultra-performance liquid chromatography-mass spectrometry based comprehensive metabolomics strategy was developed,including the extraction,separation,identification,and statistical analysis.The results showed that different types lycopodium alkaloids could be separated at different time-windows,which was helpful for further metabolite identification.Peak4388 and peak3954 were metabolite biomarkers for the different tissues according to the principle component analysis and partial least squares-discriminant analysis model.A computational tool based in-house database was also built up and used for putative identification.Of the 2354 true peaks after four-step filtration,118 peaks were putatively identified as lycopodium alkaloids by using in-house database,and four of which was identified by authentic standards.Alternatively,another computational software was used to predict the fragmentation pattern,to dereplicate the structure of identified peaks,and identified the peak3585 to N-methylhuperzine A.The integration of both computational tools could be used for more metabolites identification.

关 键 词：Huperzia serrata Different tissues Metabolomics Metabolite identification In-silico fragmentations prediction 

分 类 号：O62[理学—有机化学]