PDF(Pubmed)
Abstract：
BACKGROUND: Signal peptide (SP) engineering has proven able to improve production of many proteins yet is a laborious process that still relies on trial and error. mRNA structure around the translational start site is important in translation initiation and has rarely been considered in this context, with recent improvements in in silico mRNA structure potentially rendering it a useful predictive tool for SP selection. Here we attempt to create a method to systematically screen candidate signal peptide sequences in silico based on both their nucleotide and amino acid sequences. Several recently released computational tools were used to predict signal peptide activity (SignalP), localization target (DeepLoc) and predicted mRNA structure (MXFold2). The method was tested with Bone Morphogenetic Protein 2 (BMP2), an osteogenic growth factor used clinically for bone regeneration. It was hoped more effective BMP2 SPs could improve BMP2-based gene therapies and reduce the cost of recombinant BMP2 production.
RESULTS: Amino acid sequence analysis indicated 2,611 SPs from the TGF-β superfamily were predicted to function when attached to BMP2. mRNA structure prediction indicated structures at the translational start site were likely highly variable. The five sequences with the most accessible translational start sites, a codon optimized BMP2 SP variant and the well-established hIL2 SP sequence were taken forward to in vitro testing. The top five candidates showed non-significant improvements in BMP2 secretion in HEK293T cells. All showed reductions in secretion versus the native sequence in C2C12 cells, with several showing large and significant decreases. None of the tested sequences were able to increase alkaline phosphatase activity above background in C2C12s. The codon optimized control sequence and hIL2 SP showed reasonable activity in HEK293T but very poor activity in C2C12.
CONCLUSIONS: These results support the use of peptide sequence based in silico tools for basic predictions around signal peptide activity in a synthetic biology context. However, mRNA structure prediction requires improvement before it can produce reliable predictions for this application. The poor activity of the codon optimized BMP2 SP variant in C2C12 emphasizes the importance of codon choice, mRNA structure, and cellular context for SP activity.
RESULTS: Amino acid sequence analysis indicated 2,611 SPs from the TGF-β superfamily were predicted to function when attached to BMP2. mRNA structure prediction indicated structures at the translational start site were likely highly variable. The five sequences with the most accessible translational start sites, a codon optimized BMP2 SP variant and the well-established hIL2 SP sequence were taken forward to in vitro testing. The top five candidates showed non-significant improvements in BMP2 secretion in HEK293T cells. All showed reductions in secretion versus the native sequence in C2C12 cells, with several showing large and significant decreases. None of the tested sequences were able to increase alkaline phosphatase activity above background in C2C12s. The codon optimized control sequence and hIL2 SP showed reasonable activity in HEK293T but very poor activity in C2C12.
CONCLUSIONS: These results support the use of peptide sequence based in silico tools for basic predictions around signal peptide activity in a synthetic biology context. However, mRNA structure prediction requires improvement before it can produce reliable predictions for this application. The poor activity of the codon optimized BMP2 SP variant in C2C12 emphasizes the importance of codon choice, mRNA structure, and cellular context for SP activity.
摘要：
背景：信号肽（SP）工程已被证明能够改善许多蛋白质的生产，但这仍然是一个费力的过程，仍然依赖于反复试验。翻译起始位点周围的mRNA结构在翻译起始中很重要，在这种情况下很少被考虑，随着计算机mRNA结构的最新改进，它可能成为SP选择的有用预测工具。在这里，我们试图创建一种方法，以基于其核苷酸和氨基酸序列系统地筛选计算机中的候选信号肽序列。最近发布的几个计算工具用于预测信号肽活性（SignalP），定位靶标(DeepLoc)和预测的mRNA结构(MXFold2)。该方法用骨形态发生蛋白2（BMP2）进行了测试，临床上用于骨再生的成骨生长因子。希望更有效的BMP2SP可以改善基于BMP2的基因治疗并降低重组BMP2生产的成本。
结果：氨基酸序列分析表明，当与BMP2连接时，来自TGF-β超家族的2,611个SP具有功能。mRNA结构预测表明翻译起始位点的结构可能高度可变。具有最易接近的翻译起始位点的五个序列，密码子优化的BMP2SP变体和完善的hIL2SP序列被用于体外测试。前五个候选物显示HEK293T细胞中BMP2分泌的非显著改善。与C2C12细胞中的天然序列相比，全部显示分泌减少，有几个显示出大且显著的下降。在C2C12s中,没有一个测试序列能够增加碱性磷酸酶活性高于背景。密码子优化的对照序列和hIL2SP在HEK293T中显示出合理的活性,但在C2C12中显示出非常差的活性。
结论：这些结果支持使用基于肽序列的计算机工具，在合成生物学背景下对信号肽活性进行基本预测。然而,mRNA结构预测需要改进才能为该应用产生可靠的预测。C2C12中密码子优化的BMP2SP变体的低活性强调了密码子选择的重要性,mRNA结构，和SP活动的细胞环境。
结果：氨基酸序列分析表明，当与BMP2连接时，来自TGF-β超家族的2,611个SP具有功能。mRNA结构预测表明翻译起始位点的结构可能高度可变。具有最易接近的翻译起始位点的五个序列，密码子优化的BMP2SP变体和完善的hIL2SP序列被用于体外测试。前五个候选物显示HEK293T细胞中BMP2分泌的非显著改善。与C2C12细胞中的天然序列相比，全部显示分泌减少，有几个显示出大且显著的下降。在C2C12s中,没有一个测试序列能够增加碱性磷酸酶活性高于背景。密码子优化的对照序列和hIL2SP在HEK293T中显示出合理的活性,但在C2C12中显示出非常差的活性。
结论：这些结果支持使用基于肽序列的计算机工具，在合成生物学背景下对信号肽活性进行基本预测。然而,mRNA结构预测需要改进才能为该应用产生可靠的预测。C2C12中密码子优化的BMP2SP变体的低活性强调了密码子选择的重要性,mRNA结构，和SP活动的细胞环境。
