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LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space
Jonathan L Schmid-Burgk; Ricarda Maria Schmithausen; David Li; Ronja Hollstein; Amir Ben-Shmuel; Ofir Israeli; Shay Weiss; Nir Paran; Gero Wilbring; Jana Liebing; David Feldman; Mikolaj Slabicki; Baerbel Lippke; Esther Sib; Jacob Borrajo; Jonathan Strecker; Julia Reinhardt; Per Hoffmann; Brian Cleary; Michael Hoelzel; Markus M Noethen; Martin Exner; Kerstin U Ludwig; Aviv Regev; Feng Zhang.
Affiliation
  • Jonathan L Schmid-Burgk; Broad Institute of MIT and Harvard; Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital Bonn, 53127 Bonn, Germany
  • Ricarda Maria Schmithausen; University Hospital Bonn
  • David Li; Broad Institute of MIT and Harvard
  • Ronja Hollstein; Institute of Human Genetics, University of Bonn
  • Amir Ben-Shmuel; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona, Israel
  • Ofir Israeli; Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness Ziona, Israel
  • Shay Weiss; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona, Israel
  • Nir Paran; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona, Israel
  • Gero Wilbring; Institute of Hygiene and Public Health, University Hospital Bonn, 53127 Bonn, Germany
  • Jana Liebing; Institute for Experimental Oncology, University Hospital Bonn, 53127 Bonn, Germany
  • David Feldman; Institute for Protein Design, University of Washington
  • Mikolaj Slabicki; Broad Institute of MIT and Harvard
  • Baerbel Lippke; Institute of Human Genetics, University Hospital Bonn, 53127 Bonn, Germany
  • Esther Sib; Institute of Hygiene and Public Health, University Hospital Bonn, 53127 Bonn, Germany
  • Jacob Borrajo; Broad Institute of MIT and Harvard
  • Jonathan Strecker; Broad Institute of MIT and Harvard
  • Julia Reinhardt; Institute for Experimental Oncology, University Hospital Bonn, 53127 Bonn, Germany
  • Per Hoffmann; Institute of Human Genetics, University Hospital Bonn, 53127 Bonn, Germany and Genomics Research Group, Department of Biomedicine, University of Basel, Switzerl
  • Brian Cleary; Broad Institute of MIT and Harvard
  • Michael Hoelzel; Institute for Experimental Oncology, University Hospital Bonn, 53127 Bonn, Germany
  • Markus M Noethen; Institute of Human Genetics, University Hospital Bonn, 53127 Bonn, Germany
  • Martin Exner; Institute of Hygiene and Public Health, University Hospital Bonn, 53127 Bonn, Germany
  • Kerstin U Ludwig; Institute of Human Genetics, University Hospital Bonn, 53127 Bonn, Germany
  • Aviv Regev; MIT and Broad Inst. of MIT & Harvard
  • Feng Zhang; Broad Institute of MIT and Harvard; McGovern Institute for Brain Research at MIT
Preprint in En | PREPRINT-BIORXIV | ID: ppbiorxiv-025635
ABSTRACT
The 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.
License
cc_by_nc_nd
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Experimental_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Experimental_studies / Prognostic_studies Language: En Year: 2020 Document type: Preprint