ReviewComputational and structural biotechnology journal2012
Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals.
Review in Computational and structural biotechnology journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Extremophile Microbial Communities and Enzymes for Bioenergetic Application Based on Multi-Omics Tools.Current genomics · 2020Review
- Combinatorial application of two aldehyde oxidoreductases on isobutanol production in the presence of furfural.Journal of industrial microbiology & biotechnology · 2016Article
- Two-dimensional isobutyl acetate production pathways to improve carbon yield.Nature communications · 2015Article
- Analytics for Metabolic Engineering.Frontiers in bioengineering and biotechnology · 2015Review
- Molecular adaptation mechanisms employed by ethanologenic bacteria in response to lignocellulose-derived inhibitory compounds.International journal of biological sciences · 2013Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 Km, turnover number kcat and Ki, 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.
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Registered trials
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