Emerging engineering principles for yield improvement in microbial cell design
Metabolic Engineering has undertaken a rapid transformation in the last ten years making real progress towards the production of a wide range of molecules and fine chemicals using a designed cellular host. However, the maximization of product yields through pathway optimization is a constant and cen...
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2012-10-01
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doaj-b978e10a2a82413993f86f84ece465812020-11-24T23:48:50ZengElsevierComputational and Structural Biotechnology Journal2001-03702012-10-0134e201210016Emerging engineering principles for yield improvement in microbial cell designSantiago CombaAna ArabolazaHugo GramajoMetabolic Engineering has undertaken a rapid transformation in the last ten years making real progress towards the production of a wide range of molecules and fine chemicals using a designed cellular host. However, the maximization of product yields through pathway optimization is a constant and central challenge of this field. Traditional methods used to improve the production of target compounds from engineered biosynthetic pathways in non-native hosts include: codon usage optimization, elimination of the accumulation of toxic intermediates or byproducts, enhanced production of rate-limiting enzymes, selection of appropriate promoter and ribosome binding sites, application of directed evolution of enzymes, and chassis re-circuit. Overall, these approaches tend to be specific for each engineering project rather than a systematic practice based on a more generalizable strategy. In this mini-review, we highlight some novel and extensive approaches and tools intended to address the improvement of a target product formation, founded in sophisticated principles such as dynamic control, pathway genes modularization, and flux modeling.http://journals.sfu.ca/rncsb/index.php/csbj/article/view/csbj.201210016 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Santiago Comba Ana Arabolaza Hugo Gramajo |
spellingShingle |
Santiago Comba Ana Arabolaza Hugo Gramajo Emerging engineering principles for yield improvement in microbial cell design Computational and Structural Biotechnology Journal |
author_facet |
Santiago Comba Ana Arabolaza Hugo Gramajo |
author_sort |
Santiago Comba |
title |
Emerging engineering principles for yield improvement in microbial cell design |
title_short |
Emerging engineering principles for yield improvement in microbial cell design |
title_full |
Emerging engineering principles for yield improvement in microbial cell design |
title_fullStr |
Emerging engineering principles for yield improvement in microbial cell design |
title_full_unstemmed |
Emerging engineering principles for yield improvement in microbial cell design |
title_sort |
emerging engineering principles for yield improvement in microbial cell design |
publisher |
Elsevier |
series |
Computational and Structural Biotechnology Journal |
issn |
2001-0370 |
publishDate |
2012-10-01 |
description |
Metabolic Engineering has undertaken a rapid transformation in the last ten years making real progress towards the production of a wide range of molecules and fine chemicals using a designed cellular host. However, the maximization of product yields through pathway optimization is a constant and central challenge of this field. Traditional methods used to improve the production of target compounds from engineered biosynthetic pathways in non-native hosts include: codon usage optimization, elimination of the accumulation of toxic intermediates or byproducts, enhanced production of rate-limiting enzymes, selection of appropriate promoter and ribosome binding sites, application of directed evolution of enzymes, and chassis re-circuit. Overall, these approaches tend to be specific for each engineering project rather than a systematic practice based on a more generalizable strategy. In this mini-review, we highlight some novel and extensive approaches and tools intended to address the improvement of a target product formation, founded in sophisticated principles such as dynamic control, pathway genes modularization, and flux modeling. |
url |
http://journals.sfu.ca/rncsb/index.php/csbj/article/view/csbj.201210016 |
work_keys_str_mv |
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