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

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...

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Main Authors: Shiwen Wu, Zhen Fan, Youli Xiao
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2018-03-01
Series:Synthetic and Systems Biotechnology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405805X17301072
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author Shiwen Wu
Zhen Fan
Youli Xiao
author_facet Shiwen Wu
Zhen Fan
Youli Xiao
author_sort Shiwen Wu
collection DOAJ
description 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.
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spelling doaj.art-e841b817808c420786e68933d4ec75312024-04-16T21:41:06ZengKeAi Communications Co., Ltd.Synthetic and Systems Biotechnology2405-805X2018-03-0131445510.1016/j.synbio.2017.12.003Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrataShiwen Wu0Zhen Fan1Youli Xiao2CAS 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, ChinaCAS 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, ChinaCAS 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, ChinaQian 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.http://www.sciencedirect.com/science/article/pii/S2405805X17301072Huperzia serrataDifferent tissuesMetabolomicsMetabolite identificationIn-silico fragmentations prediction
spellingShingle Shiwen Wu
Zhen Fan
Youli Xiao
Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
Synthetic and Systems Biotechnology
Huperzia serrata
Different tissues
Metabolomics
Metabolite identification
In-silico fragmentations prediction
title Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
title_full Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
title_fullStr Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
title_full_unstemmed Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
title_short Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata
title_sort comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of huperzia serrata
topic Huperzia serrata
Different tissues
Metabolomics
Metabolite identification
In-silico fragmentations prediction
url http://www.sciencedirect.com/science/article/pii/S2405805X17301072
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AT zhenfan comprehensiverelativequantitativemetabolomicsanalysisoflycopodiumalkaloidsindifferenttissuesofhuperziaserrata
AT youlixiao comprehensiverelativequantitativemetabolomicsanalysisoflycopodiumalkaloidsindifferenttissuesofhuperziaserrata