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• W4285395243 abstract "Over the past decade, evidence has accumulated that new protein-coding genes can emerge de novo from previously non-coding DNA. Most studies have focused on large scale computational predictions of de novo protein-coding genes across a wide range of organisms. In contrast, experimental data concerning the folding and function of de novo proteins are scarce. This might be due to difficulties in handling de novo proteins in vitro, as most are short and predicted to be disordered. Here, we propose a guideline for the effective expression of eukaryotic de novo proteins in Escherichia coli. We used 11 sequences from Drosophila melanogaster and 10 from Homo sapiens, that are predicted de novo proteins from former studies, for heterologous expression. The candidate de novo proteins have varying secondary structure and disorder content. Using multiple combinations of purification tags, E. coli expression strains, and chaperone systems, we were able to increase the number of solubly expressed putative de novo proteins from 30% to 62%. Our findings indicate that the best combination for expressing putative de novo proteins in E. coli is a GST-tag with T7 Express cells and co-expressed chaperones. We found that, overall, proteins with higher predicted disorder were easier to express. STATEMENT: Today, we know that proteins do not only evolve by duplication and divergence of existing proteins but also arise from previously non-coding DNA. These proteins are called de novo proteins. Their properties are still poorly understood and their experimental analysis faces major obstacles. Here, we aim to present a starting point for soluble expression of de novo proteins with the help of chaperones and thereby enable further characterization." @default.
• W4285395243 created "2022-07-14" @default.
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• W4285395243 date "2022-07-13" @default.
• W4285395243 modified "2023-09-30" @default.
• W4285395243 title "Heterologous expression of naturally evolved putative <i>de novo</i> proteins with chaperones" @default.
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• W4285395243 doi "https://doi.org/10.1002/pro.4371" @default.
• W4285395243 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35900020" @default.
• W4285395243 hasPublicationYear "2022" @default.
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