GC-MS based metabolomics and multivariate statistical analysis of Wedelia trilobata extracts for the identification of potential phytochemical properties

Kamalrul Azlan Azizan, Nurul Haizun Abdul Ghani, Mohammad Firdaus Nawawi

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Wedelia trilobata is known as a noxious weed with potential pharmaceutical properties that can be used to treat inflammation and bacterial infections. Despite its impacts and potentials, the characterization of W. trilobata's metabolite profiles using metabolomics approach has never been described. In this study, we used a non-targeted gas chromatography mass spectrometer (GC-MS) and multivariate statistical analysis (MVA) to determine the metabolic content of W. trilobata. Metabolite extraction was carried out using solvents of methanol/water, methanol/chloroform/water, ethanol and water. Unsupervised principle component analysis (PCA) and partial least square discriminant analysis (PLSDA) were applied to evaluate grouping trends between the different solvents extracts. Upon evaluation of four different extraction solvents systems, ethanol was found to have good extraction efficiency based on metabolites contribution and separation trend observed in PCA and PLSDA. Variable importance in projection (VIP) scores revealed that separation between solvents extract were largely contributed by monosaccharides and diterpenes of resin acids of 13-cis-retinoid acid and isopimaric acid. High abundance of resin acids in W. trilobata suggested potential allelopathy properties that can have beneficial herbicides. This study presents a simple non-targeted metabolomics approach to determine the metabolite differences in W. trilobata. The findings can be used to further optimise metabolite extraction from W. trilobata.

Original languageEnglish
Pages (from-to)537-543
Number of pages7
JournalPlant OMICS
Volume8
Issue number6
Publication statusPublished - 2015

Fingerprint

Sphagneticola trilobata
metabolomics
spectrometers
phytopharmaceuticals
multivariate analysis
gas chromatography
metabolites
resin acids
extracts
discriminant analysis
least squares
principal component analysis
methanol
ethanol
noxious weeds
retinoids
water
allelopathy
acids
monosaccharides

Keywords

  • Allelopathy
  • GC-MS
  • Metabolomics
  • Wedelia trilobata

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Plant Science

Cite this

GC-MS based metabolomics and multivariate statistical analysis of Wedelia trilobata extracts for the identification of potential phytochemical properties. / Azizan, Kamalrul Azlan; Ghani, Nurul Haizun Abdul; Nawawi, Mohammad Firdaus.

In: Plant OMICS, Vol. 8, No. 6, 2015, p. 537-543.

Research output: Contribution to journalArticle

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