Metabolic Profiling of <i>Conyza sumatrensis</i> (Retz.) E. Walker from Lugazi, Uganda

<i>Conyza sumatrensis</i> is a plant of the Asteraceae family widespread in the tropical and subtropical regions of all continents. The plant is applied in folk medicine to treat malaria and helminth infections as well as other diseases. In Uganda, for example, the plant is traditionally...

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Main Authors: Christina Seel, Ivan Kahwa, Hilda Ikiriza, Hannah Sofie Koller, Helene Fitzner, Susan Billig, Claudia Wiesner, Leonard Kaysser
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/10/5580
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Summary:<i>Conyza sumatrensis</i> is a plant of the Asteraceae family widespread in the tropical and subtropical regions of all continents. The plant is applied in folk medicine to treat malaria and helminth infections as well as other diseases. In Uganda, for example, the plant is traditionally used against ectoparasites and for wound healing. In this work, we describe a comprehensive analytical approach to investigate the metabolic profile of <i>C. sumatrensis</i> supported by database-assisted annotation and in silico techniques. The study aimed to analyze the metabolic profile of <i>C. sumatrensis</i> using multiple analytical techniques due to the complexity of the plant composition. Therefore, we employed a combination of thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). From the GC-MS experiments, more than 40 compounds could be annotated that had not been found in <i>C. sumatrensis</i> before. A number of these substances are known to possess relevant bioactivities, including antibacterial properties. Indeed, ethanolic extracts demonstrated antimicrobial activity against representative strains of both Gram-positive and Gram-negative bacteria, as shown by agar diffusion and microdilution assays. Using LC-MS/MS data, a feature-based molecular network was constructed to facilitate the comparison of two extraction solvents: water and ethanol. The majority of the features were detected in both of the extracts. However, some features were only detected using one of the extraction solvents. Our work provided valuable insights into the chemical profile of <i>C. sumatrensis</i> and lays the foundation for future research into its medicinal properties.
ISSN:2076-3417