Literature DB >> 31577419

Model-Assisted Fine-Tuning of Central Carbon Metabolism in Yeast through dCas9-Based Regulation.

Raphael Ferreira1,2, Christos Skrekas1,2, Alex Hedin1, Benjamín J Sánchez1,2, Verena Siewers1,2, Jens Nielsen1,2,3, Florian David1,2.   

Abstract

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.

Entities:  

Keywords:  CRISPR; biosensor; flux balance analysis; synthetic biology

Year:  2019        PMID: 31577419     DOI: 10.1021/acssynbio.9b00258

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  9 in total

1.  Fluorescence-Activated Cell Sorting as a Tool for Recombinant Strain Screening.

Authors:  Christos Skrekas; Raphael Ferreira; Florian David
Journal:  Methods Mol Biol       Date:  2022

2.  Dynamic modulation of enzyme activity by synthetic CRISPR-Cas6 endonucleases.

Authors:  Alexander A Mitkas; Mauricio Valverde; Wilfred Chen
Journal:  Nat Chem Biol       Date:  2022-04-25       Impact factor: 16.174

3.  Applications of CRISPR/Cas gene-editing technology in yeast and fungi.

Authors:  Binyou Liao; Xi Chen; Xuedong Zhou; Yujie Zhou; Yangyang Shi; Xingchen Ye; Min Liao; Ziyi Zhou; Lei Cheng; Biao Ren
Journal:  Arch Microbiol       Date:  2021-12-26       Impact factor: 2.552

4.  A genome-scale CRISPR interference guide library enables comprehensive phenotypic profiling in yeast.

Authors:  Nicholas J McGlincy; Zuriah A Meacham; Kendra K Reynaud; Ryan Muller; Rachel Baum; Nicholas T Ingolia
Journal:  BMC Genomics       Date:  2021-03-23       Impact factor: 3.969

Review 5.  Genome-scale modeling of yeast metabolism: retrospectives and perspectives.

Authors:  Yu Chen; Feiran Li; Jens Nielsen
Journal:  FEMS Yeast Res       Date:  2022-02-22       Impact factor: 2.796

6.  Biosensor-Coupled In Vivo Mutagenesis and Omics Analysis Reveals Reduced Lysine and Arginine Synthesis To Improve Malonyl-Coenzyme A Flux in Saccharomyces cerevisiae.

Authors:  Chenxi Qiu; Mingtao Huang; Yishan Hou; Huilin Tao; Jianzhi Zhao; Yu Shen; Xiaoming Bao; Qingsheng Qi; Jin Hou
Journal:  mSystems       Date:  2022-03-01       Impact factor: 7.324

7.  Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae.

Authors:  Olena P Ishchuk; Iván Domenzain; Benjamín J Sánchez; Facundo Muñiz-Paredes; José L Martínez; Jens Nielsen; Dina Petranovic
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-18       Impact factor: 12.779

8.  Genetic circuit design automation for yeast.

Authors:  Ye Chen; Shuyi Zhang; Eric M Young; Timothy S Jones; Douglas Densmore; Christopher A Voigt
Journal:  Nat Microbiol       Date:  2020-08-03       Impact factor: 17.745

9.  Engineering transcription factor-based biosensors for repressive regulation through transcriptional deactivation design in Saccharomyces cerevisiae.

Authors:  Chenxi Qiu; Xiaoxu Chen; Reheman Rexida; Yu Shen; Qingsheng Qi; Xiaoming Bao; Jin Hou
Journal:  Microb Cell Fact       Date:  2020-07-20       Impact factor: 5.328

  9 in total

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