Effect of storage time on metabolite profile and alpha-glucosidase inhibitory activity of Cosmos caudatus leaves – GCMS based metabolomics approach

• Main Authors: Neda Javadi, Faridah Abas, Ahmed Mediani, Azizah Abd Hamid, Alfi Khatib, Sanimah Simoh, Khozirah Shaari
• Format: Article
• Language: English
• Published: Elsevier 2015-09-01
• Series: Journal of Food and Drug Analysis
• Subjects: Cosmos caudatus; GC-MS; MVDA; OPLS; storage
• Online Access: http://www.sciencedirect.com/science/article/pii/S1021949815000332

Cosmos caudatus, which is a commonly consumed vegetable in Malaysia, is locally known as “Ulam Raja”. It is a local Malaysian herb traditionally used as a food and medicinal herb to treat several maladies. Its bioactive or nutritional constituents consist of a wide range of metabolites, including glucosinolates, phenolics, amino acids, organic acids, and sugars. However, many of these metabolites are not stable and easily degraded or modified during storage. In order to investigate the metabolomics changes occurring during post-harvest storage, C. caudatus samples were subjected to seven different storage times (0 hours, 2 hours, 4 hours, 6 hours, 8 hours, 10 hours, and 12 hours) at room temperature. As the model experiment, the metabolites identified by gas chromatography-mass spectrometry (GC-MS) were correlated with α-glucosidase inhibitory activity analyzed with multivariate data analysis (MVDA) to find out the variation among samples and metabolites contributing to the activity. Orthogonal partial least squares (OPLS) analysis was applied to investigate the metabolomics changes. A profound chemical alteration, both in primary and secondary metabolites, was observed. The α-tocopherol, catechin, cyclohexen-1-carboxylic acid, benzoic acid, myo-inositol, stigmasterol, and lycopene compounds were found to be the discriminating metabolites at early storage; however, sugars such as sucrose, α-d-galactopyranose, and turanose were detected, which was attributed to the discriminating metabolites for late storage. The result shows that the MVDA method is a promising technique to identify biomarker compounds relative to storage at different times.