SARS-CoV-2 RNA Extraction Using Magnetic Beads for Rapid Large-Scale Testing by RT-qPCR and RT-LAMP
Steffen Klein, Thorsten G. Müller, Dina Khalid, Vera Sonntag-Buck, Anke‐Mareil Heuser, Bärbel Glass, Matthias Meurer, Ivonne Morales, Angelika Schillak, Andrew Freistaedter, Ina Ambiel, Sophie L. Winter, Liv Zimmermann, Tamara Naumoska, Felix Bubeck, Daniel Kirrmaier, Stephanie Ullrich, Isabel Barreto Miranda, Simon Anders, Dirk Grimm
- 发表年份
- 2020
- 引用次数
- 119
- 访问权限
- 开放获取
摘要
Rapid large-scale testing is essential for controlling the ongoing pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The standard diagnostic pipeline for testing SARS-CoV-2 presence in patients with an ongoing infection is predominantly based on pharyngeal swabs, from which the viral RNA is extracted using commercial kits, followed by reverse transcription and quantitative PCR detection. As a result of the large demand for testing, commercial RNA extraction kits may be limited and, alternatively, non-commercial protocols are needed. Here, we provide a magnetic bead RNA extraction protocol that is predominantly based on in-house made reagents and is performed in 96-well plates supporting large-scale testing. Magnetic bead RNA extraction was benchmarked against the commercial QIAcube extraction platform. Comparable viral RNA detection sensitivity and specificity were obtained by fluorescent and colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) using a primer set targeting the N gene, as well as RT-qPCR using a primer set targeting the E gene, showing that the RNA extraction protocol presented here can be combined with a variety of detection methods at high throughput. Importantly, the presented diagnostic workflow can be quickly set up in a laboratory without access to an automated pipetting robot.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992