Improving ribonucleic acid production in Saccharomyces pastorianus via in silico genome‐scale metabolic network model

Abstract

AbstractRibonucleic acid (RNA) and its degradation products are important biomolecules widely used in the food and pharmaceutical industries for their flavoring and nutritional functions. In this study, we used a genome‐scale metabolic network model (GSMM) to explore genetic targets for nucleic acid synthesis in a Saccharomyces pastorianus strain (G03). Yeast 8.5.0 was used as the base model, which accurately predicted G03's growth. Using OptForce, we found that overexpression of ARO8 and ATP1 among six different strategies increased the RNA content of G03 by 58.0% and 74.8%, respectively. We also identified new metabolic targets for improved RNA production using a modified GSMM called TissueModel, constructed using the GIMME transcriptome constraint tool to remove low‐expressed reactions in the model. After running OptKnock, the RNA content of G03‐△BNA1 and G03‐△PMA1 increased by 44.6% and 39.8%, respectively, compared to G03. We suggest that ATP1, ARO8, BNA1, and PMA1 regulate cell fitness, which affects RNA content. This study is the first to identify strategies for RNA overproduction using GSMM and to report that regulation of ATP1, ARO8, BNA1, and PMA1 can increase RNA content in S. pastorianus. These findings also provide valuable knowledge on model reconstruction for S. pastorianus.