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通过无缝克隆和体外翻译相结合构建 T7 噬菌体随机肽文库。

Construction of a T7 phage random peptide library by combining seamless cloning with in vitro translation.

机构信息

Department of Biological Chemistry, Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.

出版信息

J Biochem. 2023 Dec 20;175(1):85-93. doi: 10.1093/jb/mvad077.

Abstract

T7 phage libraries displaying random peptides are powerful tools for screening peptide sequences that bind to various target molecules. The T7 phage system has the advantage of less biased peptide distribution compared to the M13 phage system. However, the construction of T7 phage DNA is challenging due to its long 36 kb linear DNA. Furthermore, the diversity of the libraries depends strongly on the efficiency of commercially available packaging extracts. To address these issues, we examined the combination of seamless cloning with cell-free translation systems. Seamless cloning technologies have been widely used to construct short circular plasmid DNA, and several recent studies showed that cell-free translation can achieve more diverse phage packaging. In this study, we combined these techniques to construct four libraries (CX7C, CX9C, CX11C and CX13C) with different random regions lengths. The libraries thus obtained all showed diversity > 109 plaque forming units (pfu). Evaluating our libraries with an anti-FLAG monoclonal antibody yielded the correct epitope sequence. The results indicate that our libraries are useful for screening peptide epitopes against antibodies. These findings suggest that our system can efficiently construct T7 phage libraries with greater diversity than previous systems.

摘要

T7 噬菌体展示随机肽文库是筛选与各种靶分子结合的肽序列的强大工具。与 M13 噬菌体系统相比,T7 噬菌体系统具有肽分布偏差较小的优势。然而,由于其长 36kb 的线性 DNA,T7 噬菌体 DNA 的构建具有挑战性。此外,文库的多样性强烈依赖于商业可用包装提取物的效率。为了解决这些问题,我们研究了无缝克隆与无细胞翻译系统的结合。无缝克隆技术已广泛用于构建短的环状质粒 DNA,最近的几项研究表明,无细胞翻译可以实现更具多样性的噬菌体包装。在这项研究中,我们将这些技术结合起来构建了四个具有不同随机区域长度的文库(CX7C、CX9C、CX11C 和 CX13C)。获得的文库多样性均大于 10^9 噬菌斑形成单位(pfu)。用抗 FLAG 单克隆抗体评估我们的文库得到了正确的表位序列。结果表明,我们的文库可用于筛选针对抗体的肽表位。这些发现表明,我们的系统可以高效地构建比以前的系统具有更大多样性的 T7 噬菌体文库。

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