Reconstruction of a Genome-Scale Metabolic Model for Aspergillus oryzae Engineered Strain: A Potent Computational Tool for Enhancing Cordycepin Production

TL;DR

A new computational model for a modified Aspergillus oryzae strain helps boost cordycepin production, a valuable compound for pharmaceuticals.

Contribution

The first genome-scale metabolic model for a cordycepin-producing Aspergillus oryzae strain is reconstructed and validated.

Findings

The GSMM iNR1684 includes 1684 genes and 1947 reactions with high coverage and was validated experimentally.

In silico analysis identified key gene targets in pentose phosphate and one-carbon metabolism pathways for enhancing cordycepin production.

Optimal carbon-to-nitrogen ratio of 11.6:1 was found to maximize cordycepin production in A. oryzae.

Abstract

Cordycepin, a bioactive adenosine analog, holds promise in pharmaceutical and health product development. However, large-scale production remains constrained by the limitations of natural producers, Cordyceps spp. Herein, we report the reconstruction of the first genome-scale metabolic model (GSMM) for a cordycepin-producing strain of recombinant Aspergillus oryzae. The model, iNR1684, incorporated 1684 genes and 1947 reactions with 93% gene-protein-reaction coverage, which was validated by the experimental biomass composition and growth rate. In silico analyses identified key gene amplification targets in the pentose phosphate and one-carbon metabolism pathways, indicating that folate metabolism is crucial for enhancing cordycepin production. Nutrient optimization simulations revealed that chitosan, D-glucosamine, and L-aspartate preferentially supported cordycepin biosynthesis. Additionally, a carbon-to-nitrogen ratio of 11.6:1 was identified and experimentally validated to maximize production, higher than that reported for Cordyceps militaris. These findings correspond to a faster growth rate, enhanced carbon assimilation, and broader substrate utilization by A. oryzae. This study demonstrates the significant role of GSMM in uncovering rational engineering strategies and provides a quantitative framework for precision fermentation, offering scalable and sustainable solutions for industrial cordycepin production.

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