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首页> 美国卫生研究院文献>Nucleic Acids Research >Incomplete factorial and response surface methods in experimental design: yield optimization of tRNA(Trp) from in vitro T7 RNA polymerase transcription.
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Incomplete factorial and response surface methods in experimental design: yield optimization of tRNA(Trp) from in vitro T7 RNA polymerase transcription.

机译：实验设计中不完整的阶乘和响应面方法：从体外T7 RNA聚合酶转录优化tRNA（Trp）的产量。

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摘要

We have studied the yield of Escherichia coli tRNA(Trp) obtained from in vitro T7 RNA polymerase transcription using incomplete factorial and response surface methods. Incomplete factorial experiments were first used to estimate the relative impact of six variables on the yield of tRNA(Trp). Fifteen trials were performed according to a balanced and randomized design. The correlation between observed yield and all experimental variables was identified by stepwise multiple linear regression analysis. The concentrations of T7 RNA polymerase, DNA template, NTP and MgCl2 proved to be significantly correlated with the yield of tRNA(Trp). We then optimized the yield with respect to each of these four variables simultaneously with a designed, response surface experiment based on the Hardin-Sloane minimum prediction variance algorithm. Twenty experiments were performed, in duplicate, to sample the quadratic surface relating the yield to the four significant variables. Coefficients of the quadratic function with all two-factor interactions were evaluated by stepwise regression using least squares, and significant coefficients were retained. Partial differentiation of the resulting quadratic model showed it to possess an optimum. Transcription performed at the corresponding conditions yielded 6-fold more tRNA(Trp) than the initial conditions, confirming the predictive value of the experimentally determined response surface.
机译：我们已经研究了使用不完全因子分解和响应表面方法从体外T7 RNA聚合酶转录获得的大肠杆菌tRNA（Trp）的产量。首先使用不完全因子分析来估计六个变量对tRNA（Trp）产量的相对影响。根据平衡和随机设计进行了15次试验。通过逐步多元线性回归分析确定观察到的产量与所有实验变量之间的相关性。 T7 RNA聚合酶，DNA模板，NTP和MgCl2的浓度被证明与tRNA（Trp）的产量显着相关。然后，我们使用基于Hardin-Sloane最小预测方差算法的设计响应面实验，同时针对这四个变量中的每个变量优化了产量。一式两份进行了20个实验，以采样将产量与四个重要变量相关的二次曲面。使用最小二乘法通过逐步回归来评估具有所有两因素相互作用的二次函数的系数，并且保留了重要的系数。所得二次模型的偏微分表明它具有最优值。在相应条件下进行的转录产生的tRNA（Trp）比初始条件多6倍，证实了实验确定的响应表面的预测值。

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