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Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases

Enzymes empower chemical industries and are the keystone for metabolic engineering. For example, linalool synthases are indispensable for the biosynthesis of linalool, an important fragrance used in 60–80% cosmetic and personal care products. However, plant linalool synthases have low activities whi...

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Autores principales: Zhang, Congqiang, Chen, Xixian, Lee, Raphael Tze Chuen, T, Rehka, Maurer-Stroh, Sebastian, Rühl, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890063/
https://www.ncbi.nlm.nih.gov/pubmed/33597725
http://dx.doi.org/10.1038/s42003-021-01715-z
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author Zhang, Congqiang
Chen, Xixian
Lee, Raphael Tze Chuen
T, Rehka
Maurer-Stroh, Sebastian
Rühl, Martin
author_facet Zhang, Congqiang
Chen, Xixian
Lee, Raphael Tze Chuen
T, Rehka
Maurer-Stroh, Sebastian
Rühl, Martin
author_sort Zhang, Congqiang
collection PubMed
description Enzymes empower chemical industries and are the keystone for metabolic engineering. For example, linalool synthases are indispensable for the biosynthesis of linalool, an important fragrance used in 60–80% cosmetic and personal care products. However, plant linalool synthases have low activities while expressed in microbes. Aided by bioinformatics analysis, four linalool/nerolidol synthases (LNSs) from various Agaricomycetes were accurately predicted and validated experimentally. Furthermore, we discovered a linalool synthase (Ap.LS) with exceptionally high levels of selectivity and activity from Agrocybe pediades, ideal for linalool bioproduction. It effectively converted glucose into enantiopure (R)-linalool in Escherichia coli, 44-fold and 287-fold more efficient than its bacterial and plant counterparts, respectively. Phylogenetic analysis indicated the divergent evolution paths for plant, bacterial and fungal linalool synthases. More critically, structural comparison provided catalytic insights into Ap.LS superior specificity and activity, and mutational experiments validated the key residues responsible for the specificity.
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spelling pubmed-78900632021-03-03 Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases Zhang, Congqiang Chen, Xixian Lee, Raphael Tze Chuen T, Rehka Maurer-Stroh, Sebastian Rühl, Martin Commun Biol Article Enzymes empower chemical industries and are the keystone for metabolic engineering. For example, linalool synthases are indispensable for the biosynthesis of linalool, an important fragrance used in 60–80% cosmetic and personal care products. However, plant linalool synthases have low activities while expressed in microbes. Aided by bioinformatics analysis, four linalool/nerolidol synthases (LNSs) from various Agaricomycetes were accurately predicted and validated experimentally. Furthermore, we discovered a linalool synthase (Ap.LS) with exceptionally high levels of selectivity and activity from Agrocybe pediades, ideal for linalool bioproduction. It effectively converted glucose into enantiopure (R)-linalool in Escherichia coli, 44-fold and 287-fold more efficient than its bacterial and plant counterparts, respectively. Phylogenetic analysis indicated the divergent evolution paths for plant, bacterial and fungal linalool synthases. More critically, structural comparison provided catalytic insights into Ap.LS superior specificity and activity, and mutational experiments validated the key residues responsible for the specificity. Nature Publishing Group UK 2021-02-17 /pmc/articles/PMC7890063/ /pubmed/33597725 http://dx.doi.org/10.1038/s42003-021-01715-z Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zhang, Congqiang
Chen, Xixian
Lee, Raphael Tze Chuen
T, Rehka
Maurer-Stroh, Sebastian
Rühl, Martin
Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title_full Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title_fullStr Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title_full_unstemmed Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title_short Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
title_sort bioinformatics-aided identification, characterization and applications of mushroom linalool synthases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890063/
https://www.ncbi.nlm.nih.gov/pubmed/33597725
http://dx.doi.org/10.1038/s42003-021-01715-z
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