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Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)

In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vi...

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Autores principales: Haines, Matthew C, Storch, Marko, Oyarzún, Diego A, Stan, Guy-Bart, Baldwin, Geoff S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445825/
https://www.ncbi.nlm.nih.gov/pubmed/32995542
http://dx.doi.org/10.1093/synbio/ysz019
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author Haines, Matthew C
Storch, Marko
Oyarzún, Diego A
Stan, Guy-Bart
Baldwin, Geoff S
author_facet Haines, Matthew C
Storch, Marko
Oyarzún, Diego A
Stan, Guy-Bart
Baldwin, Geoff S
author_sort Haines, Matthew C
collection PubMed
description In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vivo. To address the first of these limitations, we developed Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR). LigASERR is scalable, amenable to automation and requires less time to implement compared to alternative methods. To improve the predictability of experiments, we modeled the underlying selection process, predicting experimental outcomes based on sequence and population parameters. We applied this new methodology and model to the enrichment of a known, in vitro-selected sequence from a bespoke library. Prior to implementing selection, conditions were optimized and target sequence dynamics accurately predicted for the majority of the experiment. In addition to enriching the target sequence, we identified two new, theophylline-activated ribozymes. Notably, all three sequences yielded riboswitches functional in Escherichia coli, suggesting LigASERR and similar in vitro selection methods can be utilized for generating functional riboswitches in this organism.
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spelling pubmed-74458252020-09-28 Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR) Haines, Matthew C Storch, Marko Oyarzún, Diego A Stan, Guy-Bart Baldwin, Geoff S Synth Biol (Oxf) Research Article In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vivo. To address the first of these limitations, we developed Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR). LigASERR is scalable, amenable to automation and requires less time to implement compared to alternative methods. To improve the predictability of experiments, we modeled the underlying selection process, predicting experimental outcomes based on sequence and population parameters. We applied this new methodology and model to the enrichment of a known, in vitro-selected sequence from a bespoke library. Prior to implementing selection, conditions were optimized and target sequence dynamics accurately predicted for the majority of the experiment. In addition to enriching the target sequence, we identified two new, theophylline-activated ribozymes. Notably, all three sequences yielded riboswitches functional in Escherichia coli, suggesting LigASERR and similar in vitro selection methods can be utilized for generating functional riboswitches in this organism. Oxford University Press 2019-07-08 /pmc/articles/PMC7445825/ /pubmed/32995542 http://dx.doi.org/10.1093/synbio/ysz019 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
Haines, Matthew C
Storch, Marko
Oyarzún, Diego A
Stan, Guy-Bart
Baldwin, Geoff S
Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title_full Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title_fullStr Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title_full_unstemmed Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title_short Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)
title_sort riboswitch identification using ligase-assisted selection for the enrichment of responsive ribozymes (ligaserr)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445825/
https://www.ncbi.nlm.nih.gov/pubmed/32995542
http://dx.doi.org/10.1093/synbio/ysz019
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