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Biosensor-based enzyme engineering approach applied to psicose biosynthesis

Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost...

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Autores principales: Armetta, Jeremy, Berthome, Rose, Cros, Antonin, Pophillat, Celine, Colombo, Bruno Maria, Pandi, Amir, Grigoras, Ioana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445875/
https://www.ncbi.nlm.nih.gov/pubmed/32995548
http://dx.doi.org/10.1093/synbio/ysz028
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author Armetta, Jeremy
Berthome, Rose
Cros, Antonin
Pophillat, Celine
Colombo, Bruno Maria
Pandi, Amir
Grigoras, Ioana
author_facet Armetta, Jeremy
Berthome, Rose
Cros, Antonin
Pophillat, Celine
Colombo, Bruno Maria
Pandi, Amir
Grigoras, Ioana
author_sort Armetta, Jeremy
collection PubMed
description Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework’s efficiency.
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spelling pubmed-74458752020-09-28 Biosensor-based enzyme engineering approach applied to psicose biosynthesis Armetta, Jeremy Berthome, Rose Cros, Antonin Pophillat, Celine Colombo, Bruno Maria Pandi, Amir Grigoras, Ioana Synth Biol (Oxf) Research Article Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework’s efficiency. Oxford University Press 2019-12-02 /pmc/articles/PMC7445875/ /pubmed/32995548 http://dx.doi.org/10.1093/synbio/ysz028 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Armetta, Jeremy
Berthome, Rose
Cros, Antonin
Pophillat, Celine
Colombo, Bruno Maria
Pandi, Amir
Grigoras, Ioana
Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title_full Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title_fullStr Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title_full_unstemmed Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title_short Biosensor-based enzyme engineering approach applied to psicose biosynthesis
title_sort biosensor-based enzyme engineering approach applied to psicose biosynthesis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445875/
https://www.ncbi.nlm.nih.gov/pubmed/32995548
http://dx.doi.org/10.1093/synbio/ysz028
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