First-principles model of optimal translation factors stoichiometry
Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2021-09-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/69222 |
| _version_ | 1828383107607166976 |
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| author | Jean-Benoît Lalanne Gene-Wei Li |
| author_facet | Jean-Benoît Lalanne Gene-Wei Li |
| author_sort | Jean-Benoît Lalanne |
| collection | DOAJ |
| description | Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry. |
| first_indexed | 2024-12-10T04:44:10Z |
| format | Article |
| id | doaj.art-6fe6bffc37214d3ea29f0dc69876c9e3 |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-12-10T04:44:10Z |
| publishDate | 2021-09-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-6fe6bffc37214d3ea29f0dc69876c9e32022-12-22T02:01:48ZengeLife Sciences Publications LtdeLife2050-084X2021-09-011010.7554/eLife.69222First-principles model of optimal translation factors stoichiometryJean-Benoît Lalanne0https://orcid.org/0000-0001-8753-0669Gene-Wei Li1https://orcid.org/0000-0001-7036-8511Department of Biology, Massachusetts Institute of Technology, Cambridge, United States; Department of Physics, Massachusetts Institute of Technology, Cambridge, United StatesDepartment of Biology, Massachusetts Institute of Technology, Cambridge, United StatesEnzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry.https://elifesciences.org/articles/69222predictive modelmRNA translation factorsexpression stoichiometry |
| spellingShingle | Jean-Benoît Lalanne Gene-Wei Li First-principles model of optimal translation factors stoichiometry eLife predictive model mRNA translation factors expression stoichiometry |
| title | First-principles model of optimal translation factors stoichiometry |
| title_full | First-principles model of optimal translation factors stoichiometry |
| title_fullStr | First-principles model of optimal translation factors stoichiometry |
| title_full_unstemmed | First-principles model of optimal translation factors stoichiometry |
| title_short | First-principles model of optimal translation factors stoichiometry |
| title_sort | first principles model of optimal translation factors stoichiometry |
| topic | predictive model mRNA translation factors expression stoichiometry |
| url | https://elifesciences.org/articles/69222 |
| work_keys_str_mv | AT jeanbenoitlalanne firstprinciplesmodelofoptimaltranslationfactorsstoichiometry AT geneweili firstprinciplesmodelofoptimaltranslationfactorsstoichiometry |