UHPLC-Q-Orbitrap HRMS-based Untargeted Metabolomics of Sida rhombifolia Leaves and Stem Extracts

Alfi Hudatul Karomah (Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, Indonesia)
Mohamad Rafi (Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, Indonesia. Tropical Biopharmaca Research Center-Institute of Research and Community Services, IPB University, Bogor 16128, Indonesia. Advanced Research)
Dewi Anggraini Septaningsih (Advanced Research Laboratory-Institute of Research and Community Services, IPB University, Bogor 16680, Indonesia)
Auliya Ilmiawati (Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680, Indonesia. Tropical Biopharmaca Research Center-Institute of Research and Community Services, IPB University, Bogor 16128, Indonesia)
Utami Dyah Syafitri (Department of Statistics and Data Sciences, Faculty of Mathematics and Natural Sciences, IPB University, Bogor 16680 Indonesia)
Nanik Siti Aminah (Department of Chemistry, Faculty of Science and Technology, Universitas Airlangga, Surabaya 60286, Indonesia)
Muhamad Insanu (School of Pharmacy, Institut Teknologi Bandung, Bandung 40132, Indonesia)
Abdul Rohman (Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia)

HAYATI Journal of Biosciences
Vol. 30 No. 4 (2023): July 2023

Sida rhombifolia, also known as sidaguri in Indonesia, is a medicinal plant commonly used as a herbal medicine because of its metabolite and biological activities. One of the several factors that affect plant metabolite composition and concentration is the use of plant parts. In this study, the experiment aimed to identify the metabolite profile in the leaves and stem extracts of S. rhombifolia using UHPLC-Q-Orbitrap HRMS-based untargeted metabolomics. The samples were distinguished by principal component analysis (PCA). Extraction of metabolites was conducted by sonication for approximately 30 min with 70% ethanol as the extraction solvent; 28 metabolites were identified. Seven metabolites were identified only in the leaves, three were identified only in the stems, and 18 other metabolites were identified in both the leaves and stems. These metabolites were categorized as flavonoids, triterpenoids, alkaloids, coumarins, phenolic aldehydes, phenolic acids, ecdysteroids, fatty acids, and monoterpene lactones. Based on the classification results, PCA grouped the leaves and stem extracts of S. rhombifolia using the peak area variables of the identified metabolites.