Turmeric Rhizome Metabolomic Study Using Liquid Chromatography-Mass Spectrometry

Abstract

Metabolomic approach by liquid chromatography-mass spectrometry (LC-MS) instrument was performed to determine metabolite profile of turmeric (Curcuma longa) from some areas. In this study, samples turmeric were collected from 5 different areas, those are Karanganyar, Nagrak, Ngawi, Bogor, and Sukabumi. LC-MS chromatograms were processed using MZmine and The Unscrambler software. MZmine processed LC-MS chromatograms into mass array. Identification of metabolites prediction was performed by comparing the measured accurate mass of peak as result of mass array with definite accurate mass of the turmeric derived metabolites which found in dictionary of natural product (dnp.chemnetbase.com), and through literature studies from biosynthetic pathway of curcuma (metabolite mapping). Principle component analysis (PCA) with The Unscrambler software grouped turmeric samples based on different area and determined identifier metabolite. Bioactivity property which have been tested in this research was antioxidant activity of turmeric. The result showed 121 total metabolites were identified from curcuma and composition of the metabolite content was different based on the origin of the samples. The PCA showed grouping based on sample repetition for Sukabumi and Karanganyar turmeric whereas there was no grouping for other turmeric origins. The highest antioxidant activity was shown by Sukabumi turmeric with IC50 value 47.63 mg/mL. The Sukabumi turmeric sample can be identified by the absence of calebin A content that had m/z value 384,939.

Pendekatan metabolomik dengan instrumen kromatografi cair-spektroskopi massa (LC-MS) dilakukan untuk mengetahui profil metabolit kunyit (Curcuma longa) berdasarkan perbedaan daerah sumber. Pada penelitian ini, sampel kunyit yang digunakan berasal dari 5 daerah yang berbeda, yaitu Karanganyar, Nagrak, Ngawi, Bogor, dan Sukabumi. Kromatogram LC-MS diolah menggunakan perangkat lunak MZmine dan The Unscrambler. MZmine mengolah kromatogram LC-MS menjadi bentuk mass array. Identifikasi pendugaan metabolit dilakukan dengan membandingkan massa akurat puncak terukur hasil mass array dengan massa akurat pasti senyawa metabolit turunan kurkuma yang terdapat pada dictionary natural product (dnp.chemnetbase.com), serta melalui studi pustaka jalur biosintesis genus kurkuma (peta metabolit). Analisis komponen utama (PCA) dengan perangkat lunak The Unscrambler mengelompokkan sampel kunyit berdasarkan perbedaan daerah sumber serta menentukan metabolit penciri. Sifat bioaktivitas yang diuji ialah aktivitas antioksidan kunyit. Hasil identifikasi menunjukkan total 121 metabolit di dalam genus kurkuma teridentifikasi dan ada perbedaan komposisi kandungan metabolit berdasarkan daerah sumber sampel. Pola pengelompokan hasil PCA menunjukkan pengelompokan berdasarkan ulangan sampel untuk kunyit Sukabumi dan Karanganyar sedangkan tidak mengelompok untuk sampel kunyit daerah sumber lain. Aktivitas antioksidan paling tinggi ditunjukkan oleh kunyit Sukabumi dengan nilai IC50 47.63 μg/mL. Sampel kunyit Sukabumi dapat dicirikan dengan tidak adanya kandungan kalebin A yang memiliki nilai m/z 384,939.