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Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design
BACKGROUND: HMF oxidase (HMFO) from Methylovorus sp. is a recently characterized flavoprotein oxidase. HMFO is a remarkable enzyme as it is able to oxidize 5-hydroxymethylfurfural (HMF) into 2,5-furandicarboxylic acid (FDCA): a catalytic cascade of three oxidation steps. Because HMF can be formed fr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5831843/ https://www.ncbi.nlm.nih.gov/pubmed/29507608 http://dx.doi.org/10.1186/s13068-018-1051-x |
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author | Martin, Caterina Ovalle Maqueo, Amaury Wijma, Hein J. Fraaije, Marco W. |
author_facet | Martin, Caterina Ovalle Maqueo, Amaury Wijma, Hein J. Fraaije, Marco W. |
author_sort | Martin, Caterina |
collection | PubMed |
description | BACKGROUND: HMF oxidase (HMFO) from Methylovorus sp. is a recently characterized flavoprotein oxidase. HMFO is a remarkable enzyme as it is able to oxidize 5-hydroxymethylfurfural (HMF) into 2,5-furandicarboxylic acid (FDCA): a catalytic cascade of three oxidation steps. Because HMF can be formed from fructose or other sugars and FDCA is a polymer building block, this enzyme has gained interest as an industrially relevant biocatalyst. RESULTS: To increase the robustness of HMFO, a requirement for biotechnological applications, we decided to enhance its thermostability using the recently developed FRESCO method: a computational approach to identify thermostabilizing mutations in a protein structure. To make this approach even more effective, we now developed a new and facile gene shuffling approach to rapidly combine stabilizing mutations in a one-pot reaction. This allowed the identification of the optimal combination of seven beneficial mutations. The created thermostable HMFO mutant was further studied as a biocatalyst for the production of FDCA from HMF and was shown to perform significantly better than the original HMFO. CONCLUSIONS: The described new gene shuffling approach quickly discriminates stable and active multi-site variants. This makes it a very useful addition to FRESCO. The resulting thermostable HMFO variant tolerates the presence of cosolvents and also remained thermotolerant after introduction of additional mutations aimed at improving the catalytic activity. Due to its stability and catalytic efficiency, the final HMFO variant appears to be a promising candidate for industrial scale production of FDCA from HMF. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13068-018-1051-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5831843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58318432018-03-05 Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design Martin, Caterina Ovalle Maqueo, Amaury Wijma, Hein J. Fraaije, Marco W. Biotechnol Biofuels Research BACKGROUND: HMF oxidase (HMFO) from Methylovorus sp. is a recently characterized flavoprotein oxidase. HMFO is a remarkable enzyme as it is able to oxidize 5-hydroxymethylfurfural (HMF) into 2,5-furandicarboxylic acid (FDCA): a catalytic cascade of three oxidation steps. Because HMF can be formed from fructose or other sugars and FDCA is a polymer building block, this enzyme has gained interest as an industrially relevant biocatalyst. RESULTS: To increase the robustness of HMFO, a requirement for biotechnological applications, we decided to enhance its thermostability using the recently developed FRESCO method: a computational approach to identify thermostabilizing mutations in a protein structure. To make this approach even more effective, we now developed a new and facile gene shuffling approach to rapidly combine stabilizing mutations in a one-pot reaction. This allowed the identification of the optimal combination of seven beneficial mutations. The created thermostable HMFO mutant was further studied as a biocatalyst for the production of FDCA from HMF and was shown to perform significantly better than the original HMFO. CONCLUSIONS: The described new gene shuffling approach quickly discriminates stable and active multi-site variants. This makes it a very useful addition to FRESCO. The resulting thermostable HMFO variant tolerates the presence of cosolvents and also remained thermotolerant after introduction of additional mutations aimed at improving the catalytic activity. Due to its stability and catalytic efficiency, the final HMFO variant appears to be a promising candidate for industrial scale production of FDCA from HMF. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13068-018-1051-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-01 /pmc/articles/PMC5831843/ /pubmed/29507608 http://dx.doi.org/10.1186/s13068-018-1051-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Martin, Caterina Ovalle Maqueo, Amaury Wijma, Hein J. Fraaije, Marco W. Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title | Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title_full | Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title_fullStr | Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title_full_unstemmed | Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title_short | Creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
title_sort | creating a more robust 5-hydroxymethylfurfural oxidase by combining computational predictions with a novel effective library design |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5831843/ https://www.ncbi.nlm.nih.gov/pubmed/29507608 http://dx.doi.org/10.1186/s13068-018-1051-x |
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