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Biology subjects

Poehls, J.

Publications and source records attributed to Poehls, J..

2 recordsLinked to original sources

ENVIRONMENT MODULATES PROTEIN HETEROGENEITY THROUGH TRANSCRIPTIONAL AND TRANSLATIONAL STOP CODON MISCODING

Stop codon miscoding events give rise to longer proteins, which may alter the proteins function and thereby generate short-lasting phenotypic variability from a single gene. In order to systematically assess the frequency and origin of stop codon miscoding events, we designed a library of reporters. We introduced premature stop codons into mScarlet that enabled high-throughput quantification of protein synthesis termination errors in E.coli using fluorescent microscopy. We found that under stress conditions, stop codon miscoding may occur with a rate as high as 80%, depending on the nucleotide context, suggesting that evolution frequently samples stop codon miscoding events. The analysis of selected reporters by mass spectrometry and RNA-seq showed that not only translation but also transcription errors contribute to stop codon miscoding. The RNA polymerase is more likely to misincorporate a nucleotide at premature stop codons. Proteome-wide detection of stop codon miscoding by mass spectrometry revealed that temperature regulates the expression of cryptic sequences generated by stop codon miscoding in E.coli. Overall, our findings suggest that the environment influences the accuracy of protein production, which increases protein heterogeneity when the organisms need to adapt to new conditions.

systems biology↗

Evolutionary impact of codon specific translation errors at the proteome scale

Errors in protein synthesis can lead to non-genetic phenotypic mutations, which contribute to generating a wide range of protein diversity. There are currently no methods to measure proteome-wide amino acid misincorporations in a high-throughput fashion, limiting their detection to specific sites and few codon-anticodon pairs. Therefore, it has been technically challenging to estimate the evolutionary impact of translation errors. Here, we developed a computational pipeline, integrated with a novel mechanistic model of translation errors, which can detect translation errors across organisms and conditions. We revealed hundreds of thousands of amino acid misincorporations and a rugged error landscape in datasets of E. coli and S. cerevisiae. We provide proteome-wide evidence of how codon choice can locally reduce translation errors. Our analysis indicates that the translation machinery prevents strongly deleterious misincorporations while allowing for advantageous ones, and the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates.

evolutionary biology↗