Fukuda Nobuo, Ishii Jun, Tanaka Tsutomu, Fukuda Hideki, Ohnishi Noriyuki, Kondo Akihiko
Department of Chemical Science and Engineering, Graduate School of Science and Technology, Kobe University, 1-1 Rokkodaicho, Nada-ku, Kobe 657-8501, Japan.
Biotechnol Prog. 2008 Mar-Apr;24(2):352-7. doi: 10.1021/bp070310m. Epub 2008 Mar 7.
Magnetic separation provides a relatively quick and easy-to-use method for cell isolation and protein purification. We have developed a rapid and efficient procedure to isolate yeast cells displaying a target polypeptide, namely, the Staphylococcus aureus ZZ domain, which serves as s model for protein interactions and can bind immunoglobulin G (IgG). We optimized selection of ZZ-displaying yeast cells using thermoresponsive magnetic nanoparticles. A model library was prepared by mixing various proportions of target yeast displaying the ZZ domain with control cells. Target cells in the model library that bound to the ZZ-specific binding partner, biotinylated IgG, were selected with biotinylated thermoresponsive magnetic nanoparticles using the biotin-avidin sandwich system. We determined ZZ expression levels and optimized the concentrations of both magnetic nanoparticles and avidin for efficient selection of target cells. After optimization, we successfully enriched the target cell population 4700-fold in a single round of selection. Moreover, only two rounds of selection were required to enrich the target cell population from 0.001% to nearly 100%. Our results suggest that magnetic separation will be useful for efficient exploration of novel protein-protein interactions and rapid isolation of biomolecules with novel functions.
磁分离为细胞分离和蛋白质纯化提供了一种相对快速且易于使用的方法。我们开发了一种快速高效的程序来分离展示目标多肽（即金黄色葡萄球菌ZZ结构域）的酵母细胞，该结构域可作为蛋白质相互作用的模型，并且能够结合免疫球蛋白G（IgG）。我们使用热响应性磁性纳米颗粒优化了对展示ZZ结构域的酵母细胞的筛选。通过将展示ZZ结构域的各种比例的目标酵母与对照细胞混合，制备了一个模型文库。使用生物素-抗生物素蛋白夹心系统，用生物素化的热响应性磁性纳米颗粒筛选模型文库中与ZZ特异性结合伴侣（生物素化IgG）结合的目标细胞。我们测定了ZZ的表达水平，并优化了磁性纳米颗粒和抗生物素蛋白的浓度，以有效筛选目标细胞。优化后，我们在一轮筛选中成功地将目标细胞群体富集了4700倍。此外，仅需两轮筛选就能将目标细胞群体从0.001%富集到近100%。我们的结果表明，磁分离将有助于高效探索新型蛋白质-蛋白质相互作用，并快速分离具有新功能的生物分子。
