High throughput quantification of short nucleic acid samples by capillary electrophoresis with automated data processing.
High throughput quantification of short nucleic acid samples by capillary electrophoresis with automated data processing.
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DOI：
10.1016/j.ab.2021.114239
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发表时间：
2021-09-15
影响因子：
2.9
通讯作者：
Johnson KA
中科院分区：
文献类型：
--
作者：
Dangerfield TL;Huang NZ;Johnson KA
核酸酶催化活性的分析对于许多应用至关重要，从生物技术到寻找抗病毒药物。基于平板凝胶电泳定量 DNA 和 RNA 反应产物的常用分析方法在通量、速度和准确性方面受到限制。在这里，我们报告了使用基于毛细管电泳和荧光检测的 DNA 测序仪器分离和定量短核酸反应产物的高通量方法的优化。这些方法提供单碱基分辨率，无需大量样品制备。此外，我们还表明我们的系统的实用性扩展到了 RNA 产品的定量。现代仪器的效率和可靠性大大提高了通量，但由于毛细管之间的迁移时间变化而导致的复杂性要求我们开发计算机程序来标准化数据并量化自动动力学分析的产物。这里介绍的方法极大地提高了样品通量和准确性，并且应该适用于许多核酸酶。
Analysis of catalytic activity of nucleic acid enzymes is crucial for many applications, ranging from biotechnology to the search for antiviral drugs. Commonly used analytical methods for quantifying DNA and RNA reaction products based on slab-gel electrophoresis are limited in throughput, speed, and accuracy. Here we report the optimization of high throughput methods to separate and quantify short nucleic acid reaction products using DNA sequencing instruments based on capillary electrophoresis with fluorescence detection. These methods afford single base resolution without requiring extensive sample preparation. Additionally, we show that the utility of our system extends to quantifying RNA products. The efficiency and reliability of modern instruments offers a large increase in throughput but complications due to variations in migration times between capillaries required us to develop a computer program to normalize the data and quantify the products for automated kinetic analysis. The methods presented here greatly increase sample throughput and accuracy and should be applicable to many nucleic acid enzymes.
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影响因子：
14.9
作者：
te Velthuis AJ;Arnold JJ;Cameron CE;van den Worm SH;Snijder EJ
通讯作者：
Snijder EJ
Biopython：用于计算分子生物学和生物信息学的免费 Python 工具。
DOI：
10.1093/bioinformatics/btp163
发表时间：
2009-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者：
de Hoon MJ
影响因子：
14.9
作者：
Greenough L;Schermerhorn KM;Mazzola L;Bybee J;Rivizzigno D;Cantin E;Slatko BE;Gardner AF
通讯作者：
Gardner AF
影响因子：
2.9
作者：
Jia, YP;Patel, SS
通讯作者：
Patel, SS
影响因子：
4.8
作者：
Anand, Vasanti Subramanian;Patel, Smita S.
通讯作者：
Patel, Smita S.