融合蛋白
生物
融合基因
基因
计算生物学
重叠延伸聚合酶链反应
分子生物学
遗传学
重组DNA
作者
Andrew V. Kralicek,Mazdak Radjainia,Nazratul A.B. Mohamad Ali,Colm Carraher,Richard D. Newcomb,Alok K. Mitra
标识
DOI:10.1016/j.pep.2011.06.006
摘要
N-terminal fusion tags that enhance translation initiation or protein solubility are often used to facilitate protein overexpression. As the optimal tag for a given target protein cannot be predicted a priori, valuable time can be lost in cloning and manipulating the corresponding gene to generate different fusion constructs for expression analysis. We have developed a cell-free strategy that consolidates these steps, enabling the utility of a panel of nine fusion-tags to be determined within one to two days. This approach exploits the fact that PCR-amplified DNA can be used as a template for cell-free protein synthesis. Overlap/extension PCR using the TEV protease site as the overlap region allows the fusion of different T7 promoter (T7p)-tag-TEV DNA fragments with a TEV-gene-T7 terminator (T7ter) fragment. For tag sequences where the TEV site is not compatible, a short C₃G₃ repeat (CGr) sequence can be used as the overlap region. The resulting T7p-tag-TEV-gene-T7ter constructs are then used as templates for PCR-directed cell-free protein synthesis to identify which tag-TEV-gene fusion protein produces the highest amount of soluble protein. We have successfully applied this approach to the overexpression of the Adiponectin hypervariable domain (AHD). Five of the nine N-terminal fusion tags tested enabled the synthesis of soluble recombinant protein. The best of these was the Peptidyl-prolylcis-trans isomerise B (PpiB) fusion tag which produces 1mg/ml amounts of soluble fusion protein. PpiB is an example of a new class of fusion tag known as the "stress-responsive proteins". Our results suggest that this cell-free fusion-tag expression screen facilitates the rapid identification of suitable fusion-tags that overcome issues such as poor expression and insolubility, often encountered using conventional approaches.
科研通智能强力驱动
Strongly Powered by AbleSci AI