Literature DB >> 25238571

Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae.

Mingji Li1, Irina Borodina2.   

Abstract

Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Entities:  

Keywords:  S. cerevisiae; chemicals; metabolic engineering; synthetic biology; yeast

Mesh:

Substances:

Year:  2015        PMID: 25238571     DOI: 10.1111/1567-1364.12213

Source DB:  PubMed          Journal:  FEMS Yeast Res        ISSN: 1567-1356            Impact factor:   2.796


  30 in total

1.  Xylitol production by genetically modified industrial strain of Saccharomyces cerevisiae using glycerol as co-substrate.

Authors:  Anushree B Kogje; Anand Ghosalkar
Journal:  J Ind Microbiol Biotechnol       Date:  2017-02-10       Impact factor: 3.346

2.  Metabolic Modeling of Wine Fermentation at Genome Scale.

Authors:  Sebastián N Mendoza; Pedro A Saa; Bas Teusink; Eduardo Agosin
Journal:  Methods Mol Biol       Date:  2022

Review 3.  Toward Methanol-Based Biomanufacturing: Emerging Strategies for Engineering Synthetic Methylotrophy in Saccharomyces cerevisiae.

Authors:  Philip A Kelso; Louise K M Chow; Alex C Carpenter; Ian T Paulsen; Thomas C Williams
Journal:  ACS Synth Biol       Date:  2022-07-17       Impact factor: 5.249

4.  Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0.

Authors:  Benjamín Sánchez; Mihail Anton; Iván Domenzain; Eduard J Kerkhoven; Aarón Millán-Oropeza; Céline Henry; Verena Siewers; John P Morrissey; Nikolaus Sonnenschein; Jens Nielsen
Journal:  Nat Commun       Date:  2022-06-30       Impact factor: 17.694

5.  Synthetic biology for fibres, adhesives and active camouflage materials in protection and aerospace.

Authors:  Aled D Roberts; William Finnigan; Emmanuel Wolde-Michael; Paul Kelly; Jonny J Blaker; Sam Hay; Rainer Breitling; Eriko Takano; Nigel S Scrutton
Journal:  MRS Commun       Date:  2019-04-24       Impact factor: 2.566

6.  Production of para-aminobenzoic acid from different carbon-sources in engineered Saccharomyces cerevisiae.

Authors:  Nils J H Averesch; Gal Winter; Jens O Krömer
Journal:  Microb Cell Fact       Date:  2016-05-26       Impact factor: 5.328

7.  Production of 3-hydroxypropionic acid from glucose and xylose by metabolically engineered Saccharomyces cerevisiae.

Authors:  Kanchana R Kildegaard; Zheng Wang; Yun Chen; Jens Nielsen; Irina Borodina
Journal:  Metab Eng Commun       Date:  2015-10-31

8.  CRISPR-Cas system enables fast and simple genome editing of industrial Saccharomyces cerevisiae strains.

Authors:  Vratislav Stovicek; Irina Borodina; Jochen Forster
Journal:  Metab Eng Commun       Date:  2015-03-20

9.  Recent advances in synthetic biology of cyanobacteria for improved chemicals production.

Authors:  Fen Wang; Yuanyuan Gao; Guang Yang
Journal:  Bioengineered       Date:  2020-12       Impact factor: 3.269

10.  MESSI: metabolic engineering target selection and best strain identification tool.

Authors:  Kang Kang; Jun Li; Boon Leong Lim; Gianni Panagiotou
Journal:  Database (Oxford)       Date:  2015-08-08       Impact factor: 3.451

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