Integrative Transcriptomic and Target Metabolite Analysis as a New Tool for Designing Metabolic Engineering in Yeast

Precision fermentation processes, especially when using edited microorganisms, demand accuracy in the bioengineering process to maximize the desired outcome and to avoid adverse effects. The selection of target sites to edit using CRISPR/Cas9 can be complex, resulting in non-controlled consequences. Therefore, the use of multi-omics strategies can help in the design, selection and efficiency of genetic editing. In this study, we present a multi-omics approach based on targeted metabolite analysis and transcriptomics for the designing of CRISPR/Cas9 in baker's yeast as a more efficient strategy to select editing regions. Multi-omics shows potential to reveal new metabolic bottlenecks and to elucidate new metabolic fluxes, which could be a key factor in minimizing the metabolic burden in edited microorganisms. In our model, we focus our attention on the isoprenoid synthesis due to their industrial interest. Targeted metabolite detection combined with a transcriptomic analysis revealed hydroxymethylglutaryl-CoA reductases (HMGs) as the best target gene to induce an increase in isoprenoid synthesis. Thus, an extra copy of HMG1 was introduced using, for the first time, the synthetic UADH1 promoter. The multi-omics analysis of the recombinant strain results in an accurate assessment of yeast behavior during the most important growth phases, highlighting the metabolic burden, Crabtree effect or the diauxic shift during culture.