MOLECULAR CHARACTERIZATION OF SECONDARY METABOLITE PATHWAYS IN INDIGENOUS BOTANICAL SPECIES
DOI:
https://doi.org/10.4238/txqm2g16Keywords:
Malaxis acuminata, secondary metabolites, transcriptome annotation, KEGG pathways, medicinal orchidAbstract
Malaxis acuminata was evaluated as a representative indigenous medicinal botanical species to characterize transcriptome-derived secondary metabolite pathway potential. This study used a publicly available de novo transcriptome annotation dataset containing transcript/scaffold identifiers, KEGG orthology identifiers, pathway annotations, protein accessions, alignment scores, and E-values. The dataset was cleaned, standardized, and screened for secondary metabolite associated pathways using terms related to phenylpropanoid, flavonoid, stilbenoid, gingerol, steroid, terpenoid, diterpenoid, alkaloid, tryptophan, phenylalanine, and zeatin metabolism. Descriptive pathway analysis identified 147 transcript-level annotation records, including 130 unique KEGG orthology identifiers and 70 pathway names. Among these, 23 records were associated with secondary metabolite biosynthesis or precursor metabolism, representing 10 pathway categories. Phenylalanine metabolism was the most represented pathway, followed by stilbenoid, diarylheptanoid, and gingerol biosynthesis. Pathway-class analysis showed that phenolic and phenylpropanoid-related pathways accounted for 60.9% of secondary metabolite-associated records, followed by alkaloid-related, terpenoid/steroid-related, flavonoid-related, and phytohormone-related pathways. High-confidence annotations were observed for stilbenoid/gingerol biosynthesis, zeatin biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis, and flavone/flavonol biosynthesis. These findings indicate diverse molecular pathway potential in M. acuminata, with dominant phenylalanine-derived and phenolic biosynthetic signatures. The analysis supports transcriptome annotation as a useful approach for molecular characterization of secondary metabolite pathways in non model indigenous medicinal plants. However, findings require future targeted validation using expression profiling, metabolomics, and enzyme assays.
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