Pólo TerRa, São Carlos Institute of Physics, University of São Paulo, São Carlos, São Paulo, Brazil.
Unit for Drug Discovery, Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, São Paulo, Brazil.
PLoS One. 2022 Jul 25;17(7):e0271403. doi: 10.1371/journal.pone.0271403. eCollection 2022.
Structural biology projects are highly dependent on the large-scale expression of soluble protein and, for this purpose, heterologous expression using bacteria or yeast as host systems is usually employed. In this scenario, some of the parameters to be optimized include (i) those related to the protein construct, such as the use of a fusion protein, the choice of an N-terminus fusion/tag or a C-terminus fusion/tag; (ii) those related to the expression stage, such as the concentration and selection of inducer agent and temperature expression and (iii) the choice of the host system, which includes the selection of a prokaryotic or eukaryotic cell and the adoption of a strain. The optimization of some of the parameters related to protein expression, stage (ii), is straightforward. On the other hand, the determination of the most suitable parameters related to protein construction requires a new cycle of gene cloning, while the optimization of the host cell is less straightforward. Here, we evaluated a scalable approach for the screening of host cells for protein expression in a structural biology pipeline. We evaluated four Escherichia coli strains looking for the best yield of soluble heterologous protein expression using the same strategy for protein construction and gene cloning and comparing it to our standard strain, Rosetta 2 (DE3). Using a liquid handling device (robot), E. coli pT-GroE, Lemo21(DE3), Arctic Express (DE3), and Rosetta Gami 2 (DE3) strains were screened for the maximal yield of soluble heterologous protein recovery. For the genes used in this experiment, the Arctic Express (DE3) strain resulted in better yields of soluble heterologous proteins. We propose that screening of host cell/strain is feasible, even for smaller laboratories and the experiment as proposed can easily be scalable to a high-throughput approach.
结构生物学项目高度依赖于可溶性蛋白的大规模表达，为此，通常使用细菌或酵母作为宿主系统进行异源表达。在这种情况下，需要优化的一些参数包括：（i）与蛋白质构建相关的参数，例如使用融合蛋白、选择 N 端融合/标签或 C 端融合/标签；（ii）与表达阶段相关的参数，例如诱导剂浓度和选择、表达温度；（iii）宿主系统的选择，包括选择原核或真核细胞以及采用菌株。一些与蛋白质表达阶段（ii）相关的参数的优化是直接的。另一方面，确定与蛋白质构建最相关的参数需要新的基因克隆循环，而宿主细胞的优化则不那么直接。在这里，我们评估了一种用于结构生物学管道中蛋白质表达的宿主细胞筛选的可扩展方法。我们评估了四种大肠杆菌菌株，使用相同的蛋白质构建和基因克隆策略寻找最佳可溶性异源蛋白表达产量，并将其与我们的标准菌株 Rosetta 2（DE3）进行比较。使用液体处理设备（机器人），对 E. coli pT-GroE、Lemo21(DE3)、Arctic Express(DE3) 和 Rosetta Gami 2(DE3) 菌株进行了筛选，以获得最大产量的可溶性异源蛋白回收。对于本实验中使用的基因，Arctic Express(DE3)菌株产生的可溶性异源蛋白产量更好。我们提出，宿主细胞/菌株的筛选是可行的，即使对于较小的实验室，并且所提出的实验可以很容易地扩展到高通量方法。
