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Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals
Microbial biocatalysts such as Escherichia coli and Saccharomyces cerevisiae have been extensively subjected to Metabolic Engineering for the fermentative production of biorenewable fuels and chemicals. This often entails the introduction of new enzymes, deletion of unwanted enzymes and efforts to f...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology (RNCSB) Organization
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962213/ https://www.ncbi.nlm.nih.gov/pubmed/24688665 http://dx.doi.org/10.5936/csbj.201210005 |
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author | Jarboe, Laura R. Liu, Ping Kautharapu, Kumar Babu Ingram, Lonnie O. |
author_facet | Jarboe, Laura R. Liu, Ping Kautharapu, Kumar Babu Ingram, Lonnie O. |
author_sort | Jarboe, Laura R. |
collection | PubMed |
description | Microbial biocatalysts such as Escherichia coli and Saccharomyces cerevisiae have been extensively subjected to Metabolic Engineering for the fermentative production of biorenewable fuels and chemicals. This often entails the introduction of new enzymes, deletion of unwanted enzymes and efforts to fine-tune enzyme abundance in order to attain the desired strain performance. Enzyme performance can be quantitatively described in terms of the Michaelis-Menten type parameters K(m), turnover number k(cat) and K(i), which roughly describe the affinity of an enzyme for its substrate, the speed of a reaction and the enzyme sensitivity to inhibition by regulatory molecules. Here we describe examples of where knowledge of these parameters have been used to select, evolve or engineer enzymes for the desired performance and enabled increased production of biorenewable fuels and chemicals. Examples include production of ethanol, isobutanol, 1-butanol and tyrosine and furfural tolerance. The Michaelis-Menten parameters can also be used to judge the cofactor dependence of enzymes and quantify their preference for NADH or NADPH. Similarly, enzymes can be selected, evolved or engineered for the preferred cofactor preference. Examples of exporter engineering and selection are also discussed in the context of production of malate, valine and limonene. |
format | Online Article Text |
id | pubmed-3962213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Research Network of Computational and Structural Biotechnology (RNCSB) Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-39622132014-03-31 Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals Jarboe, Laura R. Liu, Ping Kautharapu, Kumar Babu Ingram, Lonnie O. Comput Struct Biotechnol J Mini Reviews Microbial biocatalysts such as Escherichia coli and Saccharomyces cerevisiae have been extensively subjected to Metabolic Engineering for the fermentative production of biorenewable fuels and chemicals. This often entails the introduction of new enzymes, deletion of unwanted enzymes and efforts to fine-tune enzyme abundance in order to attain the desired strain performance. Enzyme performance can be quantitatively described in terms of the Michaelis-Menten type parameters K(m), turnover number k(cat) and K(i), which roughly describe the affinity of an enzyme for its substrate, the speed of a reaction and the enzyme sensitivity to inhibition by regulatory molecules. Here we describe examples of where knowledge of these parameters have been used to select, evolve or engineer enzymes for the desired performance and enabled increased production of biorenewable fuels and chemicals. Examples include production of ethanol, isobutanol, 1-butanol and tyrosine and furfural tolerance. The Michaelis-Menten parameters can also be used to judge the cofactor dependence of enzymes and quantify their preference for NADH or NADPH. Similarly, enzymes can be selected, evolved or engineered for the preferred cofactor preference. Examples of exporter engineering and selection are also discussed in the context of production of malate, valine and limonene. Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2012-10-31 /pmc/articles/PMC3962213/ /pubmed/24688665 http://dx.doi.org/10.5936/csbj.201210005 Text en © Jarboe et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. |
spellingShingle | Mini Reviews Jarboe, Laura R. Liu, Ping Kautharapu, Kumar Babu Ingram, Lonnie O. Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title | Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title_full | Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title_fullStr | Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title_full_unstemmed | Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title_short | Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
title_sort | optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals |
topic | Mini Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962213/ https://www.ncbi.nlm.nih.gov/pubmed/24688665 http://dx.doi.org/10.5936/csbj.201210005 |
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