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ICodon customizes gene expression based on the codon composition.

ABSTRACT: Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon ( www.iCodon.org ), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, frog, and fish. Users can predict the mRNA stability of any coding sequence based on its codon composition and subsequently generate more stable (optimized) or unstable (deoptimized) variants encoding for the same protein. Further, we show that codon optimality predictions correlate with both mRNA stability using a massive reporter library and expression levels using fluorescent reporters and analysis of endogenous gene expression in zebrafish embryos and/or human cells. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.

SUBMITTER: Diez M

PROVIDER: S-EPMC9287306 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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iCodon customizes gene expression based on the codon composition.

Diez Michay M Medina-Muñoz Santiago Gerardo SG Castellano Luciana Andrea LA da Silva Pescador Gabriel G Wu Qiushuang Q Bazzini Ariel Alejandro AA

Scientific reports 20220715 1

Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon ( www.iCodon.org ), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, fro ...[more]

PMID: 35840631

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Project description:Goose astroviruses (GoAstVs) are causative agents that account for fatal infection of goslings characterized by visceral urate deposition, resulting in severe economic losses in major goose-producing regions in China since 2017. In this study, we sought to unravel the intrinsic properties associated with adaptation and evolution in the host environment of GoAstVs. Consistent results from phylogenetic analysis and correspondence analysis performed on the codon usage patterns (CUPs) reveal 2 clusters of GoAstVs, namely, GoAstV-1 and GoAstV-2. However, multiple similar compositional characteristics were found, despite the high divergence between GoAstV-1 and GoAstV-2. Studies on the base composition of GoAstVs reveal an A/U bias, indicating a compositional constraint, while natural selection prevailed in determining the CUPs in the virus genome based on our neutrality plot analysis, reflecting high adaptive pressure to fit the host environment. Codon adaptation index (CAI) analysis revealed a higher degree of fitness to the CUPs of the corresponding host for GoAstVs than avian influenza virus and betacoronaviruses, which may be a favorable factor contributing to the high pathogenicity and wide distribution of GoAstVs in goslings. In addition, GoAstVs were less adapted to ducks and chickens, with significantly lower CAI values than to geese, which may be a reason for the different prevalence of GoAstVs among these species. Extensive investigations on dinucleotide distribution revealed a significant suppression of the CpG and UpA motifs in the virus genome, which may facilitate adaptation to the host's innate immune system by evading surveillance. In addition, our study reported the trends of increasing fitness to the host's microenvironment for GoAstVs through increasing adaptation to host CUPs and ongoing reduction of CpG motifs in the virus genome. The present analysis deepens our understanding of the basic biology, pathogenesis, adaptation and evolutionary pattern of GoAstVs, and contributes to the development of novel antiviral strategies.

Project description:BackgroundCodon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias.ResultsIn this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris.ConclusionsCodon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

Dataset Information

ICodon customizes gene expression based on the codon composition.

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iCodon customizes gene expression based on the codon composition.

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