1. Scalable RT-LAMP-based SARS-CoV-2 testing for infection surveillance with applications in pandemic preparedness.
- Author
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Lou D, Meurer M, Ovchinnikova S, Burk R, Denzler A, Herbst K, Papaioannou IA, Duan Y, Jacobs ML, Witte V, Ürge D, Kirrmaier D, Krogemann M, Gubicza K, Boerner K, Bundschuh C, Weidner NM, Merle U, Knorr B, Welker A, Denkinger CM, Schnitzler P, Kräusslich HG, Dao Thi VL, De Allegri M, Nguyen HT, Deckert A, Anders S, and Knop M
- Subjects
- Humans, COVID-19 Testing, Clinical Laboratory Techniques methods, Pandemics prevention & control, Sensitivity and Specificity, RNA, Viral genetics, SARS-CoV-2 genetics, COVID-19 diagnosis, COVID-19 epidemiology
- Abstract
Throughout the SARS-CoV-2 pandemic, limited diagnostic capacities prevented sentinel testing, demonstrating the need for novel testing infrastructures. Here, we describe the setup of a cost-effective platform that can be employed in a high-throughput manner, which allows surveillance testing as an acute pandemic control and preparedness tool, exemplified by SARS-CoV-2 diagnostics in an academic environment. The strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated RNA extraction, and viral RNA detection using a semiquantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable with RT-qPCR. We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, analysis by colorimetry or sequencing, and communication of results. We evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. In parallel, we estimated the economic costs of setting up and running the test station. We performed > 35,000 tests, with an average turnover time of < 6 h from sample arrival to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics, which is independent of potentially limiting clinical diagnostics supply chains., (© 2023 The Authors. Published under the terms of the CC BY NC ND 4.0 license.)
- Published
- 2023
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