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Computationally-guided design and selection of high performing ribosomal active site mutants
Understanding how modifications to the ribosome affect function has implications for studying ribosome biogenesis, building minimal cells, and repurposing ribosomes for synthetic biology. However, efforts to design sequence-modified ribosomes have been limited because point mutations in the ribosoma...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825160/ https://www.ncbi.nlm.nih.gov/pubmed/36484094 http://dx.doi.org/10.1093/nar/gkac1036 |
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author | Kofman, Camila Watkins, Andrew M Kim, Do Soon Willi, Jessica A Wooldredge, Alexandra C Karim, Ashty S Das, Rhiju Jewett, Michael C |
author_facet | Kofman, Camila Watkins, Andrew M Kim, Do Soon Willi, Jessica A Wooldredge, Alexandra C Karim, Ashty S Das, Rhiju Jewett, Michael C |
author_sort | Kofman, Camila |
collection | PubMed |
description | Understanding how modifications to the ribosome affect function has implications for studying ribosome biogenesis, building minimal cells, and repurposing ribosomes for synthetic biology. However, efforts to design sequence-modified ribosomes have been limited because point mutations in the ribosomal RNA (rRNA), especially in the catalytic active site (peptidyl transferase center; PTC), are often functionally detrimental. Moreover, methods for directed evolution of rRNA are constrained by practical considerations (e.g. library size). Here, to address these limitations, we developed a computational rRNA design approach for screening guided libraries of mutant ribosomes. Our method includes in silico library design and selection using a Rosetta stepwise Monte Carlo method (SWM), library construction and in vitro testing of combined ribosomal assembly and translation activity, and functional characterization in vivo. As a model, we apply our method to making modified ribosomes with mutant PTCs. We engineer ribosomes with as many as 30 mutations in their PTCs, highlighting previously unidentified epistatic interactions, and show that SWM helps identify sequences with beneficial phenotypes as compared to random library sequences. We further demonstrate that some variants improve cell growth in vivo, relative to wild type ribosomes. We anticipate that SWM design and selection may serve as a powerful tool for rRNA engineering. |
format | Online Article Text |
id | pubmed-9825160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98251602023-01-09 Computationally-guided design and selection of high performing ribosomal active site mutants Kofman, Camila Watkins, Andrew M Kim, Do Soon Willi, Jessica A Wooldredge, Alexandra C Karim, Ashty S Das, Rhiju Jewett, Michael C Nucleic Acids Res Synthetic Biology and Bioengineering Understanding how modifications to the ribosome affect function has implications for studying ribosome biogenesis, building minimal cells, and repurposing ribosomes for synthetic biology. However, efforts to design sequence-modified ribosomes have been limited because point mutations in the ribosomal RNA (rRNA), especially in the catalytic active site (peptidyl transferase center; PTC), are often functionally detrimental. Moreover, methods for directed evolution of rRNA are constrained by practical considerations (e.g. library size). Here, to address these limitations, we developed a computational rRNA design approach for screening guided libraries of mutant ribosomes. Our method includes in silico library design and selection using a Rosetta stepwise Monte Carlo method (SWM), library construction and in vitro testing of combined ribosomal assembly and translation activity, and functional characterization in vivo. As a model, we apply our method to making modified ribosomes with mutant PTCs. We engineer ribosomes with as many as 30 mutations in their PTCs, highlighting previously unidentified epistatic interactions, and show that SWM helps identify sequences with beneficial phenotypes as compared to random library sequences. We further demonstrate that some variants improve cell growth in vivo, relative to wild type ribosomes. We anticipate that SWM design and selection may serve as a powerful tool for rRNA engineering. Oxford University Press 2022-12-09 /pmc/articles/PMC9825160/ /pubmed/36484094 http://dx.doi.org/10.1093/nar/gkac1036 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Synthetic Biology and Bioengineering Kofman, Camila Watkins, Andrew M Kim, Do Soon Willi, Jessica A Wooldredge, Alexandra C Karim, Ashty S Das, Rhiju Jewett, Michael C Computationally-guided design and selection of high performing ribosomal active site mutants |
title | Computationally-guided design and selection of high performing ribosomal active site mutants |
title_full | Computationally-guided design and selection of high performing ribosomal active site mutants |
title_fullStr | Computationally-guided design and selection of high performing ribosomal active site mutants |
title_full_unstemmed | Computationally-guided design and selection of high performing ribosomal active site mutants |
title_short | Computationally-guided design and selection of high performing ribosomal active site mutants |
title_sort | computationally-guided design and selection of high performing ribosomal active site mutants |
topic | Synthetic Biology and Bioengineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825160/ https://www.ncbi.nlm.nih.gov/pubmed/36484094 http://dx.doi.org/10.1093/nar/gkac1036 |
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