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- Enhancement of the solubility of recombinant proteins by fusion with a short-disordered peptide
- Jun Ren , Suhee Hwang , Junhao Shen , Hyeongwoo Kim , Hyunjoo Kim , Jieun Kim , Soyoung Ahn , Min-gyun Kim , Seung Ho Lee , Dokyun Na
- J. Microbiol. 2022;60(9):960-967. Published online July 14, 2022
- DOI: https://doi.org/10.1007/s12275-022-2122-z
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- 6 Web of Science
- 6 Crossref
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Abstract
- In protein biotechnology, large soluble fusion partners are widely utilized for increased yield and solubility of recombinant proteins. However, the production of additional large fusion partners poses an additional burden to the host, leading to a decreased protein yield. In this study, we identified two highly disordered short peptides that were able to increase the solubility of an artificially engineered aggregationprone protein, GFP-GFIL4, from 0.6% to 61% (D3-DP00592) and 46% (D4-DP01038) selected from DisProt database. For further confirmation, the peptides were applied to two insoluble E. coli proteins (YagA and YdiU). The peptides also enhanced solubility from 52% to 90% (YagA) and from 27% to 93% (YdiU). Their ability to solubilize recombinant proteins was comparable with strong solubilizing tags, maltosebinding protein (40 kDa) and TrxA (12 kDa), but much smaller (< 7 kDa) in size. For practical application, the two peptides were fused with a restriction enzyme, I-SceI, and they increased I-SceI solubility from 24% up to 75%. The highly disordered peptides did not affect the activity of I-SceI while I-SceI fused with MBP or TrxA displayed no restriction activity. Despite the small size, the highly disordered peptides were able to solubilize recombinant proteins as efficiently as conventional fusion tags and did not interfere with the function of recombinant proteins. Consequently, the identified two highly disordered peptides would have practical utility in protein biotechnology and industry.
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Citations
Citations to this article as recorded by
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Frontiers in Nutrition.2022;[Epub] CrossRef
- A review on computational models for predicting protein solubility
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