Hsiang Chuan-Chieh, Ng I-Son
Department of Chemical Engineering, National Cheng Kung University, Tainan 701, Taiwan.
ACS Synth Biol. 2025 May 16;14(5):1843-1852. doi: 10.1021/acssynbio.5c00245. Epub 2025 May 7.
T7 RNA polymerase (T7RNAP), orthogonal to the T7 promoter, is a powerful tool in engineered that enables the production of many different harsh enzymes. Still, it requires precise control, particularly when expressing toxic proteins. The optimized strategy for the interconnected processes of transcription (TX), translation (TL), and protein folding (FD) in the T7 system is still not well understood. Therefore, we developed a quantitative adjustment index (AI) to evaluate all regulatory factors within the "tri-synergistic TX-TL-FD" pathway to obtain high-level production of leaf-branch compost cutinase mutant (ICCM), an enzyme challenging to express in soluble form. Among six chassis (BD, B7G, BKJ, C43, C7G, and CKJ), and considering the effect of replication origin, ribosome binding site (RBS), and chaperones, we identified T7RNAP level and translation initiation region (TIR) as the primary determinants of expression efficiency. Coordinated regulation of TX-TL proved the most effective performance, thus enhancing ICCM expression by 90%. In contrast, FD optimization through temperature modulation yielded only 10% enhancement. Notably, molecular chaperones of GroELS and DnaK/J showed benefits only after achieving optimal TX-TL balance. This hierarchical framework of trisynergistic regulation in the T7 system provides a universal strategy to express complex proteins in engineered .
T7 RNA聚合酶(T7RNAP)与T7启动子正交,是工程领域中一种强大的工具,可用于生产多种不同的苛刻酶。然而,它需要精确控制,特别是在表达有毒蛋白质时。T7系统中转录(TX)、翻译(TL)和蛋白质折叠(FD)相互关联过程的优化策略仍未得到充分理解。因此,我们开发了一种定量调整指数(AI),以评估“三协同TX-TL-FD”途径中的所有调节因子,从而实现叶枝堆肥角质酶突变体(ICCM)的高水平生产,ICCM是一种难以以可溶形式表达的酶。在六个底盘(BD、B7G、BKJ、C43、C7G和CKJ)中,并考虑复制起点、核糖体结合位点(RBS)和分子伴侣的影响,我们确定T7RNAP水平和翻译起始区域(TIR)是表达效率的主要决定因素。TX-TL的协同调节被证明具有最有效的性能,从而使ICCM表达提高了90%。相比之下,通过温度调节优化FD仅使表达提高了10%。值得注意的是,GroELS和DnaK/J的分子伴侣仅在实现最佳TX-TL平衡后才显示出益处。T7系统中这种三协同调节的分层框架为在工程中表达复杂蛋白质提供了一种通用策略。