BIOINFORMATICS ANALYSIS OF SECONDARY METABOLITE BIOSYNTHETIC PATHWAYS IN MEDICINAL PLANTS

Authors

  • Muhammad Asad World Wildlife Fund for Nature-Pakistan
  • Muhammad Umair Faculty of Environmental Sciences, University of Agriculture, Dera Ismail Khan-29050, Pakistan

Keywords:

Secondary metabolism, Medicinal plants, Bioinformatics, KEGG pathway, Cytochrome P450, Network analysis

Abstract

We want to discover new drugs, carry out metabolic engineering, and synthesize phytochemicals in an environmentally friendly fashion and they require us to understand secondary metabolite production in medicinal plants.  The integrative bioinformatics approach was employed to examine the secondary metabolic pathways of five common medicinal plants, namely Catharanthus roseus, Withania somnifera, Ocimum sanctum, Artemisia annua and Curcuma longa.  High-throughput transcriptome data was annotated and mapped to KEGG and MetaCyc biosynthetic pathways on a functional basis.  It emerged that there were 20 secondary metabolite (SM) highly-expressed genes. The majority of them were related to the production of alkaloids, terpenoids and flavonoids.  The terpenoid backbone and phenylpropanoid routes exceeded the expectations (p < 0.01), significantly. They were also highly frequent among the species through GO and Pfam domain classification according to oxidoreductase or cytochrome P450 activity.  Pathway coverage was even more affirmed when it was mapped in MetaCyc mapping of SM molecules finding 20 bioactive metabolites in the four main biosynthetic processes.  The STRING was used to make protein-protein interaction networks which identified regulatory hubs which had high interaction scores like key oxidases and transferases.  Expression study of correlation shows that there are co-expressed clusters of genes which are strongly correlated with values of r above 0.85 indicating that metabolic modules are transcriptionally co-ordinated.  Overall, this research provides us with the entire genomic portraits of secondary metabolism of the medicinal plants. It also identifies potential candidates two genes and control points that can be exploited to enhance particular metabolic pathways.  Such findings form the initial platform of higher level of genome-scale metabolic modelling, synthetic biology and precision breeding techniques in efforts to enhance yield of bioactive compounds in medically used species.

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Published

2025-06-30