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Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening
The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstra...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298319/ https://www.ncbi.nlm.nih.gov/pubmed/28178357 http://dx.doi.org/10.1371/journal.pone.0171741 |
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author | Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. |
author_facet | Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. |
author_sort | Quaglia, Daniela |
collection | PubMed |
description | The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstrate its advantageous use to engineer a biocatalyst. Hot-spots for mutations were individuated in three distinct regions of Candida antarctica lipase A (Cal-A), the biocatalyst chosen as a target to demonstrate the versatility of this recombination method. The three corresponding gene segments were subjected to the most appropriate method of mutagenesis (targeted or random). Their straightforward reassembly allowed combining products of different mutagenesis methods in a single round for rapid production of a series of diverse libraries, thus facilitating directed evolution. Screening to improve discrimination of short-chain versus long-chain fatty acid substrates was aided by development of a general, automated method for visual discrimination of the hydrolysis of varied substrates by whole cells. |
format | Online Article Text |
id | pubmed-5298319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52983192017-02-17 Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. PLoS One Research Article The Golden Gate strategy entails the use of type IIS restriction enzymes, which cut outside of their recognition sequence. It enables unrestricted design of unique DNA fragments that can be readily and seamlessly recombined. Successfully employed in other synthetic biology applications, we demonstrate its advantageous use to engineer a biocatalyst. Hot-spots for mutations were individuated in three distinct regions of Candida antarctica lipase A (Cal-A), the biocatalyst chosen as a target to demonstrate the versatility of this recombination method. The three corresponding gene segments were subjected to the most appropriate method of mutagenesis (targeted or random). Their straightforward reassembly allowed combining products of different mutagenesis methods in a single round for rapid production of a series of diverse libraries, thus facilitating directed evolution. Screening to improve discrimination of short-chain versus long-chain fatty acid substrates was aided by development of a general, automated method for visual discrimination of the hydrolysis of varied substrates by whole cells. Public Library of Science 2017-02-08 /pmc/articles/PMC5298319/ /pubmed/28178357 http://dx.doi.org/10.1371/journal.pone.0171741 Text en © 2017 Quaglia et al 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 use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title | Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title_full | Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title_fullStr | Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title_full_unstemmed | Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title_short | Enzyme engineering: A synthetic biology approach for more effective library generation and automated high-throughput screening |
title_sort | enzyme engineering: a synthetic biology approach for more effective library generation and automated high-throughput screening |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298319/ https://www.ncbi.nlm.nih.gov/pubmed/28178357 http://dx.doi.org/10.1371/journal.pone.0171741 |
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