Divya Selvakumar, Gopal Ramalingam, Suganya Balan, Infant Richard Joseph Louis, Dharshan Rathinavel, Nivethitha Baluchamy, Karthikeyan Adhimoolam, Bharani Manoharan, Paranidharan Vaikuntavasan, Vellaikumar Sampathrajan, Saranya Nallusamy, Balasubramanian Arunachalam, Kalaiselvi Senthil, Senthil Natesan
Collectively, these findings reveal tissue-specific metabolite accumulation and key genes involved in MIA biosynthesis in N. cadamba. They provide valuable insights into specialized metabolism and establish a foundation for future metabolic engineering and functional genomics studies.
BACKGROUND: Neolamarckia cadamba is a medicinally important tree rich in monoterpenoid indole alkaloids (MIAs) and diverse bioactive metabolites. However, despite its therapeutic potential, the molecular mechanisms and metabolic pathways underlying MIA biosynthesis in this species remain largely unexplored.
METHODS AND RESULTS: To elucidate MIA biosynthesis in N. cadamba, we performed GC-MS based untargeted metabolomics and RNA-seq-based transcriptomic analyses of leaves, bark, and fruit tissues. A total of 281 metabolites were identified, with the fruit exhibiting the highest metabolic diversity, including 74 tissue-specific metabolites such as flavonoids, pyruvic acid, shikimic acid, and quinic acid, which are known for their anti-inflammatory, antiviral, and anticancer activities. In contrast, the bark and leaves were enriched in terpenoids, amino acids, and fatty acids, highlighting their potential roles in defence responses and growth regulation. Transcriptomic profiling and differential gene expression analysis identified several major genes involved in MIA biosynthesis, including secologanin synthase, strictosidine synthase, tryptophan decarboxylase and loganic acid O-methyltransferase. The expression patterns of these genes were further validated by quantitative real-time PCR.
CONCLUSIONS: Collectively, these findings reveal tissue-specific metabolite accumulation and key genes involved in MIA biosynthesis in N. cadamba. They provide valuable insights into specialized metabolism and establish a foundation for future metabolic engineering and functional genomics studies.