The plant kingdom contains an amazing assortment of specialized metabolites (a conservative estimate is >200.000), and thus plants are still a largely untapped source of high-value compounds. Specialized metabolites are the active molecules in medicinal plants used in traditional Chinese medicine (TCM) and Ayurveda, but also many modern plant-based medicines (e.g, taxol, vinblastine, vincristine, aspirin, artemisinin, and morphine). One of the major hurdles in the plant bioprospecting process is that the specialized metabolites responsible for the activities of interest and their biosynthetic pathways are largely unknown. Knowing the enzymes in a metabolic pathway is a prerequisite for efficient, large-scale production and improvement of these metabolites for use in medicine and industry. To reveal these pathways, we are currently exploring different approaches based on chemoinformatics, [gene expression and co-expression network analyses](https://www.frontiersin.org/articles/10.3389/fpls.2020.625035/full) to various plants showing anti-cancer and anti-bacterial activities. ![[oldenlandia.png|600]] *We collected several Oldenlandia species found around Singapore, and shown that O. corymbosa has potent anti-cancer activities. We subsequently sequenced and assembled the genome, identified the bioactive metabolite and it's targets in human cells* We are also interested in understanding how [[Abiotic stress]] regulates specialized metabolism and the [[Evolution]] of these metabolic pathways. Representative papers on specialized metabolism from our group: 1. [Transcriptomic and metabolomic characterization of antibacterial activity of _Melastoma dodecandrum_.](https://pubmed.ncbi.nlm.nih.gov/37771487/)Poh WH, Ruhazat NS, Yang LK, Shivhare D, Lim PK, Kanagasundaram Y, Rice SA, Mutwil M. Front Plant Sci (IF: 5.75; **Q1**). 2023 Sep 13;14:1205725. doi: 10.3389/fpls.2023.1205725 2. [Redesigning plant specialized metabolism with supervised machine learning using publicly available reactome data.](https://pubmed.ncbi.nlm.nih.gov/36874159/)Lim PK, Julca I, Mutwil M. Comput Struct Biotechnol J (IF: 7.27; **Q1**). 2023 Jan 18;21:1639-1650. doi: 10.1016/j.csbj.2023.01.013. 3. [Genomic, transcriptomic, and metabolomic analysis of Oldenlandia corymbosa reveals the biosynthesis and mode of action of anti-cancer metabolites.](https://pubmed.ncbi.nlm.nih.gov/36807520/)Julca I, Mutwil-Anderwald D, Manoj V, Khan Z, Lai SK, Yang LK, Beh IT, Dziekan J, Lim YP, Lim SK, Low YW, Lam YI, Tjia S, Mu Y, Tan QW, Nuc P, Choo LM, Khew G, Shining L, Kam A, Tam JP, Bozdech Z, Schmidt M, Usadel B, Kanagasundaram Y, Alseekh S, Fernie A, Li HY, Mutwil M. J Integr Plant Biol (IF: 7.06; **Q1**). 2023 Jun;65(6):1442-1466. doi: 10.1111/jipb.13469 4. [Using Gene Expression to Study Specialized Metabolism-A Practical Guide.](https://pubmed.ncbi.nlm.nih.gov/33510763/)Delli-Ponti R, Shivhare D, Mutwil M. Front Plant Sci (IF: 5.75; **Q1**). 2021 Jan 12;11:625035. doi: 10.3389/fpls.2020.625035 5. [Computational approaches to unravel the pathways and evolution of specialized metabolism.](https://pubmed.ncbi.nlm.nih.gov/32200228/) Mutwil M. Curr Opin Plant Biol (IF: 7.83; **Q1**). 2020 Jun;55:38-46. doi: 10.1016/j.pbi.2020.01.007. 6. [Expression Atlas of _Selaginella moellendorffii_ Provides Insights into the Evolution of Vasculature, Secondary Metabolism, and Roots.](https://pubmed.ncbi.nlm.nih.gov/31988262/)Ferrari C, Shivhare D, Hansen BO, Pasha A, Esteban E, Provart NJ, Kragler F, Fernie A, Tohge T, Mutwil M. Plant Cell (IF: 11.28; **Q1**). 2020 Apr;32(4):853-870. doi: 10.1105/tpc.19.00780 7. [Inferring biosynthetic and gene regulatory networks from Artemisia annua RNA sequencing data on a credit card-sized ARM computer.](https://pubmed.ncbi.nlm.nih.gov/31634636/) Tan QW, Mutwil M. Biochim Biophys Acta Gene Regul Mech (IF: 4.49; **Q2**). 2020 Jun;1863(6):194429. doi: 10.1016/j.bbagrm.2019.194429