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Optimizing the dynamics of protein expression.

ABSTRACT: 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.

SUBMITTER: Trosemeier JH

PROVIDER: S-EPMC6525252 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Optimizing the dynamics of protein expression.

Trösemeier Jan-Hendrik JH Rudorf Sophia S Loessner Holger H Hofner Benjamin B Reuter Andreas A Schulenborg Thomas T Koch Ina I Bekeredjian-Ding Isabelle I Lipowsky Reinhard R Kamp Christel C

Scientific reports 20190517 1

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 ...[more]

PMID: 31101858

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Project description:We have developed a unified, versatile vector set for expression of recombinant proteins, fit for use in any bacterial, yeast, insect or mammalian cell host. The advantage of this system is its versatility at the vector level, achieved by the introduction of a novel expression cassette. This cassette contains a unified multi-cloning site, affinity tags, protease cleavable linkers, an optional secretion signal, and common restriction endonuclease sites at key positions. This way, genes of interest and all elements of the cassette can be switched freely among the vectors, using restriction digestion and ligation without the need of polymerase chain reaction (PCR). This vector set allows rapid protein expression screening of various hosts and affinity tags. The reason behind this approach was that it is difficult to predict which expression host and which affinity tag will lead to functional expression. The new system is based on four optimized and frequently used expression systems (Escherichia coli pET, the yeast Pichia pastoris, pVL and pIEx for Spodoptera frugiperda insect cells and pLEXm based mammalian systems), which were modified as described above. The resulting vector set was named pONE series. We have successfully applied the pONE vector set for expression of the following human proteins: the tumour suppressor RASSF1A and the protein kinases Aurora A and LIMK1. Finally, we used it to express the large multidomain protein, Rho-associated protein kinase 2 (ROCK2, 164 kDa) and demonstrated that the yeast Pichia pastoris reproducibly expresses the large ROCK2 kinase with identical activity to the insect cell produced counterpart. To our knowledge this is among the largest proteins ever expressed in yeast. This demonstrates that the cost-effective yeast system can match and replace the industry-standard insect cell expression system even for large and complex mammalian proteins. These experiments demonstrate the applicability of our pONE vector set.

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Optimizing the dynamics of protein expression.

Publications

Optimizing the dynamics of protein expression.

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