Differentiation of achyranthes bidentata and cyathula officinalis using peptidomic fingerprinting with multivariate analyses

Achyranthes bidentata roots (AB) is a common traditional Chinese herb used to nourish the liver and kidney. It is often confused with Cyathula officinalis roots (CO), which is used to promote blood circulation. This study aimed to characterize cysteine-rich peptides from these two species, and const...

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Bibliographic Details
Main Author: Yap, Keni
Other Authors: James P Tam
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2018
Subjects:
Online Access:http://hdl.handle.net/10356/74167
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Institution: Nanyang Technological University
Language: English
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Summary:Achyranthes bidentata roots (AB) is a common traditional Chinese herb used to nourish the liver and kidney. It is often confused with Cyathula officinalis roots (CO), which is used to promote blood circulation. This study aimed to characterize cysteine-rich peptides from these two species, and construct a rapid and accurate classification model to differentiate them using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) coupling with multivariate analyses. Aranthide (aB1) of 3417.96 Da and cyathide (cO1) of 3472.46 Da were isolated from AB and CO, respectively. Mass shift experiment showed that both aB1 and cO1 contain 6 cysteine residues. The primary sequence of aB1 has been elucidated by de novo sequencing. Four MALDI-TOF MS-based multivariate classification methods were constructed and compared with that of ultra-performance liquid chromatography (UPLC). Results showed the classification methods from MALDI-TOF MS are comparable to that from UPLC. For both data matrices, k-nearest neighbours and partial least square-discriminant analysis provided the best classification accuracy. Classification and regression tree exhibited moderate identification power while potential function was regarded to have the least preferable classification capacity. In conclusion, MALDI-TOF MS coupled with multivariate analysis is a promising technique in discriminating AB and CO.