Planta Med 2011; 77 - PM223
DOI: 10.1055/s-0031-1282981

The use of metabolomics for the discovery of antimicrobial biomarkers from Plectranthus species indigenous to southern Africa

JE Maree 1, AM Viljoen 1, S Gibbons 2
  • 1Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001; South Africa
  • 2Department of Pharmaceutical and Biological Chemistry, The School of Pharmacy, University of London, 29–39 Brunswick Square, London WC1N 1AX, United Kingdom

For many years a reductionist approach has been followed in the evaluation of the bioactivity of medicinal plants and the subsequent isolation and identification of active compounds. Synergism and prodrug effects cannot be detected with this approach [1]. It is also a tedious and time consuming process involving isolation, dereplication of known compounds and structure elucidation [2]. A holistic approach is more appropriate in the study of herbal and traditional medicines [1]. This means that the phytomedicine is evaluated as one active ingredient or as a set of poly-phytochemicals acting synergistically [3]. The research method best suited for the holistic research concept of phytomedicine is metabolomics. Plectranthus is the largest genus of the Lamiaceae family in South Africa. The main recorded ethnobotanical use of these species is as traditional medicine for the treatment of various ailments such as digestive ailments, skin conditions and a range of infections [4]. A total of 93 leaf samples from different Plectranthus species, indigenous to southern Africa, were collected and extracted with dichloromethane followed by methanol. The antimicrobial activity of the samples was determined against various micro-organisms including Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus faecalis, Candida albicans and Cryptococcus neoformans. One-dimensional NMR and LC-MS metabolomic fingerprints were acquired for all samples. Chemometric tools were employed to identify active and less active extracts by combining and correlating NMR and LC-MS metabolomic profiles of the different samples with the MIC assay results. Putative biomarkers responsible for the antimicrobial activity of active samples were also identified.

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