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Updated: Mar 25, 2026

High-Throughput Metabolic Profiling for Model Refinements of Microalgae
Published on: December 4, 2021
Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species
Wanwipa Vongsangnak1, Amornpan Klanchui2, Iyarest Tawornsamretkit3
1Department of Zoology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand; Center for Systems Biology, Soochow University, Suzhou 215006, China; Computational Biomodelling Laboratory for Agricultural Science and Technology, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.
Abstract:
We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production.
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