Computational biotechnology guides elucidation of the biosynthesis of the plant anticancer drug camptothecin

"Computational biotechnology guides elucidation of the biosynthesis of the plant anticancer drug camptothecin"  by Emily Amor Stander, Thomas Dugé de Bernonville, Nicolas Papon and Vincent Courdavault
https://doi.org/10.1016/j.csbj.2021.06.028

Keywords : medicinal plants, Next-generation sequencing, genome mining, pharmaceuticals, biosynthetic pathway, synthetic biology
Abstract : Camptothecin is a clinically important monoterpene indole alkaloid (MIAs) used for treating various cancers. Currently, the production of this biopharmaceutical hinges on its extraction from camptothecin-producing plants, leading to high market prices and supply bottlenecks. While synthetic biology combined with metabolic approaches could represent an attractive alternative approach to manufacturing, it requires firstly a complete biosynthetic pathway elucidation, which is, unfortunately, severely missing in species naturally accumulating camptothecin. This knowledge gap can be attributed to the lack of high-quality genomic resources of medicinal plant species. In such a perspective, Yamazaki and colleagues produced the first described and experimentally validated chromosome-level plant genome assembly of Ophiorrhiza pumila, a prominent source plant of camptothecin for the pharmaceutical industry. More specifically, they have developed a method incorporating Illumina reads, PacBio single-molecule reads, optical mapping and Hi-C sequencing, followed by the experimental validation of contig orientation within scaffolds, using fluorescence in situ hybridization (FISH) analysis. This relevant strategy resulted in the most contiguous and complete de novo plant reference genome described to date, which can streamline the sequencing of new plant genomes. Further mining approaches, including integrative omics analysis, phylogenetics, gene cluster evaluation and comparative genomics were successfully used to puzzle out the evolutionary origins of MIA metabolism and revealed a short-list of high confidence MIA biosynthetic genes for functional validation.