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A genome-wide approach for identification and characterisation of metabolite-inducible systems
Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057948/ https://www.ncbi.nlm.nih.gov/pubmed/32139676 http://dx.doi.org/10.1038/s41467-020-14941-6 |
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author | Hanko, Erik K. R. Paiva, Ana C. Jonczyk, Magdalena Abbott, Matthew Minton, Nigel P. Malys, Naglis |
author_facet | Hanko, Erik K. R. Paiva, Ana C. Jonczyk, Magdalena Abbott, Matthew Minton, Nigel P. Malys, Naglis |
author_sort | Hanko, Erik K. R. |
collection | PubMed |
description | Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, we address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. We construct and validate 15 functional biosensors, provide a characterisation workflow to facilitate forward engineering efforts, exemplify their broad-host-range applicability, and demonstrate their utility in enzyme screening. Previously uncharacterised interactions between sensors and compounds of biological relevance are identified by employing the largest reported library of metabolite-responsive biosensors in an automated high-throughput screen. With the rapidly growing genomic data these innovative capabilities offer a platform to vastly increase the number of biologically detectable molecules. |
format | Online Article Text |
id | pubmed-7057948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70579482020-03-06 A genome-wide approach for identification and characterisation of metabolite-inducible systems Hanko, Erik K. R. Paiva, Ana C. Jonczyk, Magdalena Abbott, Matthew Minton, Nigel P. Malys, Naglis Nat Commun Article Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, we address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. We construct and validate 15 functional biosensors, provide a characterisation workflow to facilitate forward engineering efforts, exemplify their broad-host-range applicability, and demonstrate their utility in enzyme screening. Previously uncharacterised interactions between sensors and compounds of biological relevance are identified by employing the largest reported library of metabolite-responsive biosensors in an automated high-throughput screen. With the rapidly growing genomic data these innovative capabilities offer a platform to vastly increase the number of biologically detectable molecules. Nature Publishing Group UK 2020-03-05 /pmc/articles/PMC7057948/ /pubmed/32139676 http://dx.doi.org/10.1038/s41467-020-14941-6 Text en © The Author(s) 2020 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 Hanko, Erik K. R. Paiva, Ana C. Jonczyk, Magdalena Abbott, Matthew Minton, Nigel P. Malys, Naglis A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title | A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title_full | A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title_fullStr | A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title_full_unstemmed | A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title_short | A genome-wide approach for identification and characterisation of metabolite-inducible systems |
title_sort | genome-wide approach for identification and characterisation of metabolite-inducible systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057948/ https://www.ncbi.nlm.nih.gov/pubmed/32139676 http://dx.doi.org/10.1038/s41467-020-14941-6 |
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