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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884255/ https://www.ncbi.nlm.nih.gov/pubmed/29911198 http://dx.doi.org/10.1016/j.synbio.2017.12.003 |
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author | Wu, Shiwen Fan, Zhen Xiao, Youli |
author_facet | Wu, Shiwen Fan, Zhen Xiao, Youli |
author_sort | Wu, Shiwen |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-5884255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-58842552018-06-15 Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata Wu, Shiwen Fan, Zhen Xiao, Youli Synth Syst Biotechnol Article 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. KeAi Publishing 2017-12-26 /pmc/articles/PMC5884255/ /pubmed/29911198 http://dx.doi.org/10.1016/j.synbio.2017.12.003 Text en © 2017 Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Wu, Shiwen Fan, Zhen Xiao, Youli Comprehensive relative quantitative metabolomics analysis of lycopodium alkaloids in different tissues of Huperzia serrata |
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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884255/ https://www.ncbi.nlm.nih.gov/pubmed/29911198 http://dx.doi.org/10.1016/j.synbio.2017.12.003 |
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