Development of an optimized cell-based selection system for phage display libraries.

IF 2.5 Q3 BIOCHEMICAL RESEARCH METHODS
Biology Methods and Protocols Pub Date : 2025-02-07 eCollection Date: 2025-01-01 DOI:10.1093/biomethods/bpaf009
Malgorzata Czarnecka, Nicole Findik, Anja Schlör, Katja Hanack
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引用次数: 0

Abstract

The discovery of antibodies through phage display is significantly influenced by antigen presentation during panning, particularly for membrane-anchored proteins, which pose challenges due to their complex structures. Traditional approaches, such as whole cells expressing the target protein, often result in low antigen density and high background signals. In this study, we describe an alternative method using stably transfected cell lines that express the target antigen on their surface, regulated by an intracellular enhanced green fluorescent protein (EGFP) signal. This system enables high-throughput flow cytometry-based screening of phage display libraries to isolate human antibodies that recognize the native conformation of membrane proteins. Using human epithelial cell adhesion molecule (EpCAM) and human neuroplastin 65 (NP65) as model antigens, we established an optimized screening workflow with polyclonal phage pools. Selected EpCAM-specific single-chain variable fragments (scFvs) from a naïve library were recombinantly expressed with an IgG4 scaffold and characterized for specific binding. This approach provides an effective platform for the identification of antibodies against membrane proteins in their native state.

噬菌体展示文库优化细胞筛选系统的建立。
在筛选过程中,通过噬菌体展示发现抗体受到抗原呈递的显著影响,特别是对于膜锚定蛋白,由于其复杂的结构,这构成了挑战。传统的方法,如表达靶蛋白的全细胞,往往导致低抗原密度和高背景信号。在这项研究中,我们描述了一种替代方法,使用稳定转染的细胞系在其表面表达目标抗原,由细胞内增强的绿色荧光蛋白(EGFP)信号调节。该系统可实现基于流式细胞术的噬菌体展示文库的高通量筛选,以分离识别膜蛋白天然构象的人抗体。以人上皮细胞粘附分子(EpCAM)和人神经活素65 (NP65)为模型抗原,建立了优化的多克隆噬菌体池筛选流程。从naïve文库中选择epcam特异性单链可变片段(scFvs),用IgG4支架重组表达,并鉴定其特异性结合。该方法为鉴定天然膜蛋白抗体提供了一个有效的平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biology Methods and Protocols
Biology Methods and Protocols Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
3.80
自引率
2.80%
发文量
28
审稿时长
19 weeks
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