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Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics
The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major trans...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375613/ https://www.ncbi.nlm.nih.gov/pubmed/32649657 http://dx.doi.org/10.1371/journal.pcbi.1008038 |
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author | Levin, Doron Tuller, Tamir |
author_facet | Levin, Doron Tuller, Tamir |
author_sort | Levin, Doron |
collection | PubMed |
description | The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major translation components in the cell: ribosomes, mRNAs and tRNAs. It also includes, for the first time, fundamental aspects of translation, such as competition for ribosomes and tRNAs at a codon resolution while considering tRNAs wobble interactions and tRNA recycling. The model uses parameters that are tightly inferred from large scale measurements of translation. Furthermore, we demonstrate a robust modelling approach which relies on state-of-the-art practices of translation modelling and also provides a framework for easy generalizations. This novel approach allows simulation of thousands of mRNAs that undergo translation in the same cell with common resources such as ribosomes and tRNAs in feasible time. Based on this model, we demonstrate, for the first time, the direct importance of competition for resources on translation and its accurate modelling. An effective supply-demand ratio (ESDR) measure, which is related to translation factors such as tRNAs, has been devised and utilized to show superior predictive power in complex scenarios of heterologous gene expression. The devised model is not only more accurate than the existing models, but, more importantly, provides a framework for analyzing complex whole cell translation problems and variables that haven't been explored before, making it important in various biomedical fields. |
format | Online Article Text |
id | pubmed-7375613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73756132020-08-04 Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics Levin, Doron Tuller, Tamir PLoS Comput Biol Research Article The importance of mRNA translation models has been demonstrated across many fields of science and biotechnology. However, a whole cell model with codon resolution and biophysical dynamics is still lacking. We describe a whole cell model of translation for E. coli. The model simulates all major translation components in the cell: ribosomes, mRNAs and tRNAs. It also includes, for the first time, fundamental aspects of translation, such as competition for ribosomes and tRNAs at a codon resolution while considering tRNAs wobble interactions and tRNA recycling. The model uses parameters that are tightly inferred from large scale measurements of translation. Furthermore, we demonstrate a robust modelling approach which relies on state-of-the-art practices of translation modelling and also provides a framework for easy generalizations. This novel approach allows simulation of thousands of mRNAs that undergo translation in the same cell with common resources such as ribosomes and tRNAs in feasible time. Based on this model, we demonstrate, for the first time, the direct importance of competition for resources on translation and its accurate modelling. An effective supply-demand ratio (ESDR) measure, which is related to translation factors such as tRNAs, has been devised and utilized to show superior predictive power in complex scenarios of heterologous gene expression. The devised model is not only more accurate than the existing models, but, more importantly, provides a framework for analyzing complex whole cell translation problems and variables that haven't been explored before, making it important in various biomedical fields. Public Library of Science 2020-07-10 /pmc/articles/PMC7375613/ /pubmed/32649657 http://dx.doi.org/10.1371/journal.pcbi.1008038 Text en © 2020 Levin, Tuller 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 Levin, Doron Tuller, Tamir Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title | Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title_full | Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title_fullStr | Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title_full_unstemmed | Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title_short | Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics |
title_sort | whole cell biophysical modeling of codon-trna competition reveals novel insights related to translation dynamics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375613/ https://www.ncbi.nlm.nih.gov/pubmed/32649657 http://dx.doi.org/10.1371/journal.pcbi.1008038 |
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