Institute of Bio- and Geosciences IBG-1, Biotechnology, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany.
Institute of Biotechnology, RWTH Aachen University, 52062, Aachen, Germany.
Appl Microbiol Biotechnol. 2022 Jun;106(12):4481-4497. doi: 10.1007/s00253-022-12017-7. Epub 2022 Jun 27.
Secretion of bacterial proteins into the culture medium simplifies downstream processing by avoiding cell disruption for target protein purification. However, a suitable signal peptide for efficient secretion needs to be identified, and currently, there are no tools available to predict optimal combinations of signal peptides and target proteins. The selection of such a combination is influenced by several factors, including protein biosynthesis efficiency and cultivation conditions, which both can have a significant impact on secretion performance. As a result, a large number of combinations must be tested. Therefore, we have developed automated workflows allowing for targeted strain construction and secretion screening using two platforms. Key advantages of this experimental setup include lowered hands-on time and increased throughput. In this study, the automated workflows were established for the heterologous production of Fusarium solani f. sp. pisi cutinase in Corynebacterium glutamicum. The target protein was monitored in culture supernatants via enzymatic activity and split GFP assay. Varying spacer lengths between the Shine-Dalgarno sequence and the start codon of Bacillus subtilis signal peptides were tested. Consistent with previous work on the secretory cutinase production in B. subtilis, a ribosome binding site with extended spacer length to up to 12 nt, which likely slows down translation initiation, does not necessarily lead to poorer cutinase secretion by C. glutamicum. The best performing signal peptides for cutinase secretion with a standard spacer length were identified in a signal peptide screening. Additional insights into the secretion process were gained by monitoring secretion stress using the C. glutamicum K9 biosensor strain. KEY POINTS: • Automated workflows for strain construction and screening of protein secretion • Comparison of spacer, signal peptide, and host combinations for cutinase secretion • Signal peptide screening for secretion by C. glutamicum using the split GFP assay.
细菌蛋白分泌到培养基中简化了下游处理过程，避免了为目标蛋白纯化而进行细胞破碎。然而，需要鉴定合适的信号肽以实现有效的分泌，而目前还没有可用于预测信号肽和目标蛋白最佳组合的工具。这种组合的选择受到多种因素的影响，包括蛋白质生物合成效率和培养条件，这些因素都会对分泌性能产生重大影响。因此，必须测试大量的组合。因此，我们开发了自动化工作流程，允许使用两个平台针对目标菌株构建和分泌筛选。该实验设置的主要优点包括减少人工操作时间和提高通量。在这项研究中，建立了丝状镰刀菌 f. sp. pisi 角质酶在谷氨酸棒杆菌中的异源生产的自动化工作流程。通过酶活性和 GFP 分裂测定法监测培养上清液中的目标蛋白。测试了芽孢杆菌信号肽的 Shine-Dalgarno 序列和起始密码子之间的不同间隔长度。与芽孢杆菌分泌角质酶生产的先前工作一致，核糖体结合位点的间隔长度扩展至 12 个核苷酸，这可能会减缓翻译起始，但不一定会导致谷氨酸棒杆菌角质酶分泌减少。通过使用 GFP 分裂测定法对信号肽进行筛选，确定了角质酶分泌表现最佳的信号肽。通过监测谷氨酸棒杆菌 K9 生物传感器菌株的分泌应激，进一步了解了分泌过程。关键点： • 用于菌株构建和筛选蛋白分泌的自动化工作流程 • 比较间隔、信号肽和宿主组合对角质酶分泌的影响 • 使用 GFP 分裂测定法对谷氨酸棒杆菌的信号肽进行分泌筛选。
