Model-Assisted Fine-Tuning of Central Carbon Metabolism in Yeast through dCas9-Based Regulation
Journal article, 2019

Engineering Saccharomyces cerevisiae for industrial-scale production of valuable chemicals involves extensive modulation of its metabolism. Here, we identified novel gene expression fine-tuning set-ups to enhance endogenous metabolic fluxes toward increasing levels of acetyl-CoA and malonyl-CoA. dCas9-based transcriptional regulation was combined together with a malonyl-CoA responsive intracellular biosensor to select for beneficial set-ups. The candidate genes for screening were predicted using a genome-scale metabolic model, and a gRNA library targeting a total of 168 selected genes was designed. After multiple rounds of fluorescence-activated cell sorting and library sequencing, the gRNAs that were functional and increased flux toward malonyl-CoA were assessed for their efficiency to enhance 3-hydroxypropionic acid (3-HP) production. 3-HP production was significantly improved upon fine-tuning genes involved in providing malonyl-CoA precursors, cofactor supply, as well as chromatin remodeling.

synthetic biology

CRISPR

biosensor

flux balance analysis

Author

Raphael Ferreira

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Christos Skrekas

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Alex Hedin

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Benjamín José Sánchez

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Verena Siewers

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Jens B Nielsen

Novo Nordisk Foundation

Technical University of Denmark (DTU)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Florian David

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

ACS Synthetic Biology

2161-5063 (eISSN)

Vol. 8 11 2457-2463

Subject Categories

Biochemistry and Molecular Biology

Developmental Biology

Bioinformatics and Systems Biology

DOI

10.1021/acssynbio.9b00258

PubMed

31577419

More information

Latest update

5/26/2023