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Optimizing the dynamics of protein expression
Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific el...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525252/ https://www.ncbi.nlm.nih.gov/pubmed/31101858 http://dx.doi.org/10.1038/s41598-019-43857-5 |
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author | Trösemeier, Jan-Hendrik Rudorf, Sophia Loessner, Holger Hofner, Benjamin Reuter, Andreas Schulenborg, Thomas Koch, Ina Bekeredjian-Ding, Isabelle Lipowsky, Reinhard Kamp, Christel |
author_facet | Trösemeier, Jan-Hendrik Rudorf, Sophia Loessner, Holger Hofner, Benjamin Reuter, Andreas Schulenborg, Thomas Koch, Ina Bekeredjian-Ding, Isabelle Lipowsky, Reinhard Kamp, Christel |
author_sort | Trösemeier, Jan-Hendrik |
collection | PubMed |
description | Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences. |
format | Online Article Text |
id | pubmed-6525252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65252522019-05-29 Optimizing the dynamics of protein expression Trösemeier, Jan-Hendrik Rudorf, Sophia Loessner, Holger Hofner, Benjamin Reuter, Andreas Schulenborg, Thomas Koch, Ina Bekeredjian-Ding, Isabelle Lipowsky, Reinhard Kamp, Christel Sci Rep Article Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences. Nature Publishing Group UK 2019-05-17 /pmc/articles/PMC6525252/ /pubmed/31101858 http://dx.doi.org/10.1038/s41598-019-43857-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Trösemeier, Jan-Hendrik Rudorf, Sophia Loessner, Holger Hofner, Benjamin Reuter, Andreas Schulenborg, Thomas Koch, Ina Bekeredjian-Ding, Isabelle Lipowsky, Reinhard Kamp, Christel Optimizing the dynamics of protein expression |
title | Optimizing the dynamics of protein expression |
title_full | Optimizing the dynamics of protein expression |
title_fullStr | Optimizing the dynamics of protein expression |
title_full_unstemmed | Optimizing the dynamics of protein expression |
title_short | Optimizing the dynamics of protein expression |
title_sort | optimizing the dynamics of protein expression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525252/ https://www.ncbi.nlm.nih.gov/pubmed/31101858 http://dx.doi.org/10.1038/s41598-019-43857-5 |
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