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从本氏烟草中纯化重组蛋白用于结构研究。

Purifying recombinant proteins from Nicotiana benthamiana for structural studies.

作者信息

Lawson Aaron W, Macha Arthur, Neumann Ulla, Gunkel Monika, Chai Jijie, Behrmann Elmar, Schulze-Lefert Paul

机构信息

Department of Plant-Microbe Interactions, Max Planck Institute for Plant Breeding Research, Cologne, Germany.

University of Cologne, Faculty of Mathematics and Natural Sciences, Institute of Biochemistry, Cologne, Germany.

出版信息

Nat Protoc. 2025 Sep 9. doi: 10.1038/s41596-025-01249-2.

Abstract

Structural biology is fundamental to understanding the molecular basis of biological processes. While machine learning-based protein structure prediction has advanced considerably, experimentally determined structures remain indispensable for guiding structure-function analyses and for improving predictive modeling. However, experimental studies of protein complexes continue to pose challenges, particularly due to the necessity of high protein concentrations and purity for downstream analyses such as cryogenic electron microscopy. Transient transformation of Nicotiana benthamiana has emerged as a promising expression system for recombinant protein production, offering advantages such as low operating costs, rapid cultivation, short experimental turnaround and scalability compared with other established platforms such as insect or human cell culture systems. Here we present a versatile protocol leveraging N. benthamiana for the purification and structural analysis of protein complexes of diverse origin and composition, exemplified by six oligomeric complexes ranging from ~140 to ~660 kDa, originating from plant, vertebrate, fungal and bacterial species. In most cases, purification only requires a single epitope tag, simplifying workflows and reducing complications that come with multitag and sequential affinity purifications. The protocol enables rapid application, allowing protein sample production in fewer than 7 days. Critical parameters influencing expression and purification efficiency include codon alteration, epitope tag selection and detergent supplementation.

摘要

结构生物学对于理解生物过程的分子基础至关重要。虽然基于机器学习的蛋白质结构预测已经取得了显著进展,但实验确定的结构对于指导结构-功能分析和改进预测模型仍然不可或缺。然而,蛋白质复合物的实验研究仍然面临挑战,特别是由于下游分析(如低温电子显微镜)需要高蛋白质浓度和纯度。本氏烟草的瞬时转化已成为一种有前景的重组蛋白生产表达系统,与昆虫或人类细胞培养系统等其他成熟平台相比,具有运营成本低、培养迅速、实验周转时间短和可扩展性强等优势。在这里,我们展示了一种通用方案,利用本氏烟草对不同来源和组成的蛋白质复合物进行纯化和结构分析,以六种分子量约为140至660 kDa的寡聚复合物为例,它们分别来源于植物、脊椎动物、真菌和细菌物种。在大多数情况下,纯化仅需一个表位标签,简化了工作流程,减少了多标签和顺序亲和纯化带来的复杂性。该方案能够快速应用,在不到7天的时间内即可生产蛋白质样品。影响表达和纯化效率的关键参数包括密码子改变、表位标签选择和去污剂补充。

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