Reconstruction of Curcuma aeruginosa secondary metabolite biosynthetic pathway using omics data

Curcuma aeruginosa or temu hitam is herbaceous plant with high therapeutic values in its rhizome that is widely used in traditional medicine. However, molecular studies on the secondary metabolite biosynthetic pathway of C. aeruginosa is still limited. Hence, the aim of this study was to explore and...

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Bibliographic Details
Main Authors: Nurul-Syafika Mohamad-Fauzi, Rabiatul-Adawiah Zainal-Abidin, Mohd Waznul Adly Zaidan, Sanimah Simoh, Alizah Zainal, Zeti-Azura Mohamed-Hussein
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:http://journalarticle.ukm.my/12919/
http://journalarticle.ukm.my/12919/
http://journalarticle.ukm.my/12919/1/07%20Nurul-Syafika%20Mohamad-Fauzi.pdf
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Summary:Curcuma aeruginosa or temu hitam is herbaceous plant with high therapeutic values in its rhizome that is widely used in traditional medicine. However, molecular studies on the secondary metabolite biosynthetic pathway of C. aeruginosa is still limited. Hence, the aim of this study was to explore and reconstruct the secondary metabolite biosynthetic pathway of C. aeruginosa rhizome by integrating the metabolite profiling and transcriptomic data. A total of 81 metabolites were identified in the rhizome of C. aeruginosa; amongst others are curzerene and β-Cubebene which are potent antioxidants. A total of 28,225 unigene were obtained from the transcriptomic sequencing of C. aeruginosa rhizome and analysed to identify potential genes associated with the biosynthesis of its metabolites. Of these, 43 unigenes were identified and mapped onto five sub-pathways; i.e. carotenoid biosynthetic pathway, diterpenoid biosynthetic pathway, monoterpenoid biosynthetic pathway, terpenoid and steroid biosynthetic pathway, and sesquiterpenoid and triterpenoid biosynthetic pathway. This study demonstrated a systematic bioinformatic approach to reconstruct a metabolic pathway in the rhizome of C. aeruginosa using bioinformatic approach.