Ph.D. Candidate University of Florida Gainesville, Florida
Body of Abstract: The tree species Mitragyna speciosa, also known as Kratom, and products derived from it have gained popularity in the U.S. and Europe as alternatives for opioid pain medications and treatment of opioid addiction. Kratom leaves accumulate over 50 types of monoterpene indole alkaloids (MIA), of which ‘mitragynine’, the major leaf MIA, has received the most attention. Mitragynine is under investigation for its ability to decrease self-administration of opiates in animals, without the same potential for abuse as pharmaceutical opioids. In-vitro synthesis of MIAs is labor-intensive, environmentally unfriendly, and low-yielding, making extractions from plant material the best source. We have genotyped and quantified targeted MIAs and oxindole alkaloids from M. speciosa cultivars accumulating low to high amounts of mitragynine and different oxindole alkaloids, as well as other species including M. parvifolia and M. hirsuta. DNA barcoding and phylogenetic analysis using ribosomal ITS sequences revealed polymorphisms leading M. speciosa cultivars with lower mitragynine content to group with other mitragyna species, suggesting interspecific hybridization events might have affected metabolite profiles. By correlating transcriptomics and metabolomics of different tissues and cultivars, we attempted to unveil candidate genes involved in the biosynthesis of mitragynine and other indole and oxindole alkaloids. We have also found that quantitative and qualitative differences exist in alkaloid profiles of M. speciosa leaves over development. The MIAs speciociliatine and corynantheidine, not mitragynine, were the major alkaloids at early developmental stages. This improved understanding of the MIA profile of M. speciosa has important pharmaceutical implications, as the combined pharmacology of MIAs at opioid and adrenergic receptors in humans are important for understanding the experienced effects caused by kratom products. Future work with comparative genomics approaches will be used to characterize the genome-wide variations responsible for the divergence of the MIA pathway and diversification of MIAs.