Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli

Yankun Yang1,2small orcid_display_4pp, Guoqiang Liu1,2small orcid_display_4pp, Meng Liu2small orcid_display_4pp, Zhonghu Bai2,3small orcid_display_4pp, Xiuxia Liu2,3small orcid_display_4pp, Xiaofeng Dai2,3*small orcid_display_4pp and Wenwen Guo3,4*small orcid_display_4pp

1The Key Laboratory of Carbohydrate Chemistry and Biotechnology, School of Biotechnology, Jiangnan University, Ministry of Education, 1800 Lihu Avenue, 214122 Wuxi, PR China
2National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
3Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China
4The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, 214122 Wuxi, PR China

Article history:
Received: July 29, 2017
Accepted: January 31, 2018

Key words:
domain antibody (dAb), Escherichia coli, heterologous protein soluble expression, linear modelling, primary structure

It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80 %. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb.

*Corresponding authors:  tel2/fax2  +8651085329306
                                                    email3 (Dai), (Guo)

Paper was presented at the 7th International Forum on Industrial Bioprocessing - IFIBiop 2017, May 21-24, 2017, Wuxi, PR China

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