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Felix Bubeck

Heidelberg University

Publishes on CRISPR and Genetic Engineering, Virus-based gene therapy research, Machine Learning in Materials Science. 18 papers and 432 citations.

18Publications
432Total Citations

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Top publicationsby citations

SARS-CoV-2 RNA Extraction Using Magnetic Beads for Rapid Large-Scale Testing by RT-qPCR and RT-LAMP
Cited by 119Open Access

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.

Controlling Cells with Light and LOV
Mareike D. Hoffmann, Felix Bubeck, Roland Eils et al.|Advanced Biosystems|2018
Cited by 32Open Access

Abstract Optogenetics is a powerful method for studying dynamic processes in living cells and has advanced cell biology research over the recent past. Key to the successful application of optogenetics is the careful design of the light‐sensing module, typically employing a natural or engineered photoreceptor that links the exogenous light input to the cellular process under investigation. Light–oxygen–voltage (LOV) domains, a highly diverse class of small blue light sensors, have proven to be particularly versatile for engineering optogenetic input modules. These can function via diverse modalities, including inducible allostery, protein recruitment, dimerization, or dissociation. This study reviews recent advances in the development of LOV domain‐based optogenetic tools and their application for studying and controlling selected cellular functions. Focusing on the widely employed LOV2 domain from Avena sativa phototropin‐1, this review highlights the broad spectrum of engineering opportunities that can be explored to achieve customized optogenetic regulation. Finally, major bottlenecks in the development of optogenetic methods are discussed and strategies to overcome these with recent synthetic biology approaches are pointed out.

SARS-CoV-2 RNA extraction using magnetic beads for rapid large-scale testing by RT-qPCR and RT-LAMP
Cited by 23Open Access

Abstract 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 alternative, 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 RT-LAMP using N primers, as well as RT-qPCR using E gene primers showing that the here presented RNA extraction protocol 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.