472184 Genome-Scale Metabolic Model of a Medicinal Plant Culture System

Wednesday, November 16, 2016: 2:00 PM
Continental 8 (Hilton San Francisco Union Square)
Gregory Andrews, Chemical Engineering, Worcester Polytechnic Institut, Worcester, MA, Michael A. Henson, Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, MA and Susan C. Roberts, Chemical Engineering, University of Massachusetts, Amherst, Amherst, MA

The taxane diterpenoids are a class of compounds first isolated from species of the genus Taxus, all possessing the taxadiene core. Three taxanes, the natural product paclitaxel and its two synthetic analogs docetaxel and cabazitaxel, are currently FDA approved for the treatment of a wide variety of cancers. A number of production platforms have been used to supply market quantities of paclitaxel and semi-synthetic analog precursors dating back to the initial paclitaxel clinical trials; however, industrial scale plant cell culture has proven to be the most economic and environmentally friendly. Plant cell cultures are not optimized for taxane synthesis, plagued by slow growth rates and inconsistent product formation, necessitating novel ways to analyze and understand cellular metabolism.

Genome-scale models (GSMs) are in silico stoichiometric representations of all or part of the metabolism of a cell, tissue or organism of interest. GSMs have become indispensable tools for the study of bacterial metabolism and physiology, assessing gene essentiality and designing rational metabolic engineering strategies. However, the tool is under-utilized in the plant community, with GSMs having been constructed only for model plant systems such as Arabidopsis, maize and sorghum. Plant metabolic reconstruction is made complicated by compartmentalization, pathway duplication, and the fact that the functions of many plant genes have yet to be elucidated.

A draft Taxus GSM has been constructed and will be discussed here. Although several automated platforms have been developed for genome annotation and model construction, it was found that these platforms are not appropriate for under-characterized systems, and hence, Taxus metabolism was reconstructed using custom programs to identify and extract a set of reactions from the KEGG database that correspond to genes in an annotated Taxus transcriptome, a collection of more than 48,000 contigs present during various stages of cellular growth and metabolism. Manual curation is ongoing and comprises the addition of subcellular compartments, intracellular transporters and exchange reactions, all of which can be obtained from various databases and primary literature. Once fully curated, quantitative analysis of the constructed model can be performed with the incorporation of condition-specific transcriptome data (i.e., elicited and nonelicited, various time points, small and large sized aggregate cultures). Simulating biomass growth under various conditions allows for the study of cellular metabolism and physiology during different stages of paclitaxel synthesis and can provide key information to devise strategies to improve process performance. The final GSM will represent the first such construction of both a medicinal plant and non-model plant system.

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