Optimizing the dynamics of protein expression.
Jan-Hendrik TrösemeierSophia RudorfHolger LoessnerBenjamin HofnerAndreas ReuterThomas SchulenborgIna KochIsabelle Bekeredjian-DingReinhard LipowskyChristel KampPublished in: Scientific reports (2019)
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.
Keyphrases
- binding protein
- poor prognosis
- genome wide
- endothelial cells
- machine learning
- long non coding rna
- gene expression
- genome wide identification
- bioinformatics analysis
- deep learning
- data analysis
- electronic health record
- induced pluripotent stem cells
- protein protein
- small molecule
- skeletal muscle
- genetic diversity
- glycemic control
- neural network