Metabolomics Research at Tshwane University of Technology (TUT)

 

 

 

Phytochemical profiling is an important aspect in the quality control of herbal medicines, which ensures provision of consistently high quality botanical raw materials in the manufacture of herbal products. The phytomedicine research group, at TUT, applies plant metabolomics to study secondary metabolite networks, where changes in metabolites content are monitored, in order to document variation which has a direct impact on the biological properties of medicinal plants. Plant species, of large sample sizes are wild harvested from various geographical locations to systematically document phytochemical variation and suggest chemotypes with favourable chemical profiles for propagation and commercialisation.

In the Chemistry Department, metabolic profiling is applied to indigenous plants sourced from various geographic origin, agricultural crops and plants exposed to abiotic stress to study their tolerance mechanism. Biomarkers attributing to resistance or tolerance to various pathogens, and insect pests of agricultural produce of commercial importance are determined by multivariate data analysis. Environmental factors including metal toxicity influence on the production of secondary metabolites in plants and metabolic profiling reveals biomarkers linked to the detoxification and tolerance mechanism. Metabolic profiling of indigenous plants reveals variation in concentration and composition of fruit and essential oils from the fruit of different geographical regions.

High-quality and comprehensive phytochemical data is generated through the use of cutting-edge analytical techniques such as ultra-performance liquid chromatography coupled to mass spectrometry, gas chromatography coupled to mass spectrometry, mid-infrared and near-infrared spectroscopy, as well as nuclear magnetic resonance spectroscopy. These techniques provide comprehensive chemical information on plant metabolomes within a very short space of time. The use of various chemometrics software packages allows for multivariate analysis in an untargeted approach, to generate models that reveal chemical patterns and variability with the samples. The integration of chemical and biological activity data in biochemometrics, allows for the identification of metabolite differences between biologically active and non-active samples, deciphering putative biomarker candidates in these complex plant matrices.