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A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons
Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of transla...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538824/ https://www.ncbi.nlm.nih.gov/pubmed/26117546 http://dx.doi.org/10.1093/nar/gkv635 |
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author | Tian, Tian Salis, Howard M. |
author_facet | Tian, Tian Salis, Howard M. |
author_sort | Tian, Tian |
collection | PubMed |
description | Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. |
format | Online Article Text |
id | pubmed-4538824 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-45388242015-08-18 A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons Tian, Tian Salis, Howard M. Nucleic Acids Res Synthetic Biology and Bioengineering Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. Oxford University Press 2015-08-18 2015-06-27 /pmc/articles/PMC4538824/ /pubmed/26117546 http://dx.doi.org/10.1093/nar/gkv635 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Synthetic Biology and Bioengineering Tian, Tian Salis, Howard M. A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title | A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title_full | A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title_fullStr | A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title_full_unstemmed | A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title_short | A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
title_sort | predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons |
topic | Synthetic Biology and Bioengineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538824/ https://www.ncbi.nlm.nih.gov/pubmed/26117546 http://dx.doi.org/10.1093/nar/gkv635 |
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