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...
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ftunnottinghamrr:oai:nottingham-repository.worktribe.com:4671985 2023-05-15T13:46:22+02:00 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. Parker, Emily J. 2017-02-08 https://doi.org/10.1371/journal.pone.0171741 https://nottingham-repository.worktribe.com/file/4671985/1/Quaglia%20Enzyme%20Engineering%20A%20Synthetic https://nottingham-repository.worktribe.com/output/4671985 unknown Public Library of Science https://nottingham-repository.worktribe.com/output/4671985 PLoS ONE Volume 12 Issue 2 doi:https://doi.org/10.1371/journal.pone.0171741 https://nottingham-repository.worktribe.com/file/4671985/1/Quaglia%20Enzyme%20Engineering%20A%20Synthetic doi:10.1371/journal.pone.0171741 openAccess https://creativecommons.org/licenses/by/4.0/ CC-BY Journal Article publishedVersion 2017 ftunnottinghamrr https://doi.org/10.1371/journal.pone.0171741 2022-08-04T22:07:53Z 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. Article in Journal/Newspaper Antarc* Antarctica University of Nottingham: Repository@Nottingham Golden Gate ENVELOPE(-134.237,-134.237,59.616,59.616) PLOS ONE 12 2 e0171741 |
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University of Nottingham: Repository@Nottingham |
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ftunnottinghamrr |
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unknown |
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. |
author2 |
Parker, Emily J. |
format |
Article in Journal/Newspaper |
author |
Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. |
spellingShingle |
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 |
author_facet |
Quaglia, Daniela Ebert, Maximilian C. C. J. C. Mugford, Paul F. Pelletier, Joelle N. |
author_sort |
Quaglia, Daniela |
title |
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_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_sort |
enzyme engineering: a synthetic biology approach for more effective library generation and automated high-throughput screening |
publisher |
Public Library of Science |
publishDate |
2017 |
url |
https://doi.org/10.1371/journal.pone.0171741 https://nottingham-repository.worktribe.com/file/4671985/1/Quaglia%20Enzyme%20Engineering%20A%20Synthetic https://nottingham-repository.worktribe.com/output/4671985 |
long_lat |
ENVELOPE(-134.237,-134.237,59.616,59.616) |
geographic |
Golden Gate |
geographic_facet |
Golden Gate |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://nottingham-repository.worktribe.com/output/4671985 PLoS ONE Volume 12 Issue 2 doi:https://doi.org/10.1371/journal.pone.0171741 https://nottingham-repository.worktribe.com/file/4671985/1/Quaglia%20Enzyme%20Engineering%20A%20Synthetic doi:10.1371/journal.pone.0171741 |
op_rights |
openAccess https://creativecommons.org/licenses/by/4.0/ |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1371/journal.pone.0171741 |
container_title |
PLOS ONE |
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12 |
container_issue |
2 |
container_start_page |
e0171741 |
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1766240874956587008 |