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探索枯草芽孢杆菌中合成表达模块的非保守序列空间。

Exploring the Nonconserved Sequence Space of Synthetic Expression Modules in Bacillus subtilis.

作者信息

Sauer Christopher, Ver Loren van Themaat Emiel, Boender Leonie G M, Groothuis Daphne, Cruz Rita, Hamoen Leendert W, Harwood Colin R, van Rij Tjeerd

机构信息

Centre for Bacterial Cell Biology, Institute for Cell and Molecular Biosciences , Newcastle University , Newcastle upon Tyne NE1 7RU , United Kingdom.

DSM Biotechnology Center , P.O. Box 1, 2600 MA Delft , The Netherlands.

出版信息

ACS Synth Biol. 2018 Jul 20;7(7):1773-1784. doi: 10.1021/acssynbio.8b00110. Epub 2018 Jul 5.

Abstract

Increasing protein expression levels is a key step in the commercial production of enzymes. Predicting promoter activity and translation initiation efficiency based solely on consensus sequences have so far met with mixed results. Here, we addressed this challenge using a "brute-force" approach by designing and synthesizing a large combinatorial library comprising ∼12 000 unique synthetic expression modules (SEMs) for Bacillus subtilis. Using GFP fluorescence as a reporter of gene expression, we obtained a dynamic expression range that spanned 5 orders of magnitude, as well as a maximal 13-fold increase in expression compared with that of the already strong veg expression module. Analyses of the synthetic modules indicated that sequences at the 5'-end of the mRNA were the most important contributing factor to the differences in expression levels, presumably by preventing formation of strong secondary mRNA structures that affect translation initiation. When the gfp coding region was replaced by the coding region of the xynA gene, encoding the industrially relevant B. subtilis xylanase enzyme, only a 3-fold improvement in xylanase production was observed. Moreover, the correlation between GFP and xylanase expression levels was weak. This suggests that the differences in expression levels between the gfp and xynA constructs were due to differences in 5'-end mRNA folding and consequential differences in the rates of translation initiation. Our data show that the use of large libraries of SEMs, in combination with high-throughput technologies, is a powerful approach to improve the production of a specific protein, but that the outcome cannot necessarily be extrapolated to other proteins.

摘要

提高蛋白质表达水平是酶商业化生产中的关键步骤。仅基于共有序列预测启动子活性和翻译起始效率,目前取得的结果喜忧参半。在此,我们采用“强力”方法应对这一挑战,设计并合成了一个大型组合文库,其中包含约12000个针对枯草芽孢杆菌的独特合成表达模块(SEM)。利用绿色荧光蛋白(GFP)荧光作为基因表达的报告指标,我们获得了跨越5个数量级的动态表达范围,与原本就很强的veg表达模块相比,表达量最大提高了13倍。对合成模块的分析表明,mRNA 5'端的序列是造成表达水平差异的最重要因素,推测是通过防止形成影响翻译起始的强二级mRNA结构来实现的。当将gfp编码区替换为编码工业上相关的枯草芽孢杆菌木聚糖酶的xynA基因的编码区时,仅观察到木聚糖酶产量提高了3倍。此外,GFP和木聚糖酶表达水平之间的相关性较弱。这表明gfp和xynA构建体之间表达水平的差异是由于5'端mRNA折叠的差异以及随之而来的翻译起始速率的差异。我们的数据表明,使用大型SEM文库并结合高通量技术,是提高特定蛋白质产量的有效方法,但结果不一定能外推到其他蛋白质上。

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