LAMP-Seq: Population-Scale COVID-19 Diagnostics Using Combinatorial Barcoding
Author:
Schmid-Burgk Jonathan L.ORCID, Schmithausen Ricarda M.ORCID, Li David, Hollstein Ronja, Ben-Shmuel Amir, Israeli Ofir, Weiss Shay, Paran Nir, Wilbring Gero, Liebing Jana, Feldman David, Słabicki Mikołaj, Lippke Bärbel, Sib Esther, Borrajo Jacob, Strecker Jonathan, Reinhardt Julia, Hoffmann Per, Cleary Brian, Hölzel Michael, Nöthen Markus M.ORCID, Exner Martin, Ludwig Kerstin U., Regev Aviv, Zhang Feng
Abstract
SummaryThe ongoing SARS-CoV-2 pandemic has already caused devastating losses. Exponential spread can be slowed by social distancing and population-wide isolation measures, but those place a tremendous burden on society, and, once lifted, exponential spread can re-emerge. Regular population-scale testing, combined with contact tracing and case isolation, should help break the cycle of transmission, but current detection strategies are not capable of such large-scale processing. Here we present a protocol for LAMP-Seq, a barcoded Reverse-Transcription Loop-mediated Isothermal Amplification (RT-LAMP) method that is highly scalable. Individual samples are stabilized, inactivated, and amplified in three isothermal heat steps, generating barcoded amplicons that can be pooled and analyzed en masse by sequencing. Using unique barcode combinations per sample from a compressed barcode space enables extensive pooling, potentially further reducing cost and simplifying logistics. We validated LAMP-Seq on 28 clinical samples, empirically optimized the protocol and barcode design, and performed initial safety evaluation. Relying on world-wide infrastructure for next-generation sequencing, and in the context of population-wide sample collection, LAMP-Seq could be scaled to analyze millions of samples per day.
Publisher
Cold Spring Harbor Laboratory
Reference19 articles.
1. Fast and accurate diagnostics from highly multiplexed sequencing assays;medRxiv,2020 2. Broughton, J.P. , Deng, X. , Yu, G. , Fasching, C.L. , Singh, J. , Streithorst, J. , Granados, A. , Sotomayor-Gonzalez, A. , Zorn, K. , Gopez, A. , et al. (2020). Rapid Detection of 2019 Novel Coronavirus SARS-CoV-2 Using a CRISPR-based DETECTR Lateral Flow Assay. 1–27. 3. Chinazzi, M. , Davis, J.T. , Ajelli, M. , Gioannini, C. , Litvinova, M. , Merler, S. , Pastore y Piontti, A. , Mu, K. , Rossi, L. , Sun, K. , et al. (2020). The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science eaba9757–12. 4. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR;Euro Surveill,2020 5. An interactive web-based dashboard to track COVID-19 in real time;Lancet Infect Dis,2020
Cited by
62 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|