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LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space

View ORCID ProfileJonathan L. Schmid-Burgk, David Li, David Feldman, Mikołaj Słabicki, Jacob Borrajo, Jonathan Strecker, Brian Cleary, Aviv Regev, Feng Zhang
doi: https://doi.org/10.1101/2020.04.06.025635
Jonathan L. Schmid-Burgk
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
2McGovern Institute for Brain Research, Cambridge, MA 02139, USA
3Department of Brain and Cognitive Sciences, Cambridge, MA 02139, USA
4Department of Biological Engineering, Cambridge, MA 02139, USA
8Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital Bonn, 53127 Bonn, Germany
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  • ORCID record for Jonathan L. Schmid-Burgk
  • For correspondence: jschmid@broadinstitute.org
David Li
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
2McGovern Institute for Brain Research, Cambridge, MA 02139, USA
3Department of Brain and Cognitive Sciences, Cambridge, MA 02139, USA
4Department of Biological Engineering, Cambridge, MA 02139, USA
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David Feldman
9Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
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Mikołaj Słabicki
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
10Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
11Division of Translational Medical Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
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Jacob Borrajo
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
4Department of Biological Engineering, Cambridge, MA 02139, USA
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Jonathan Strecker
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
2McGovern Institute for Brain Research, Cambridge, MA 02139, USA
3Department of Brain and Cognitive Sciences, Cambridge, MA 02139, USA
4Department of Biological Engineering, Cambridge, MA 02139, USA
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Brian Cleary
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
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Aviv Regev
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
5Department of Biology, Cambridge, MA 02139, USA
6Klarman Cell Observatory, Cambridge, MA 02139, USA
7Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology, Cambridge, MA 02139, USA
12Howard Hughes Medical Institute, Cambridge, MA 02139, USA
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Feng Zhang
1Broad Institute of MIT and Harvard Cambridge, MA 02142, USA
2McGovern Institute for Brain Research, Cambridge, MA 02139, USA
3Department of Brain and Cognitive Sciences, Cambridge, MA 02139, USA
4Department of Biological Engineering, Cambridge, MA 02139, USA
12Howard Hughes Medical Institute, Cambridge, MA 02139, USA
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Summary

The ongoing COVID-19 pandemic has already caused devastating losses. Early evidence shows that the exponential spread of COVID-19 can be slowed by restrictive isolation measures, but these place a tremendous burden on society. Moreover, once these restrictions are lifted, the exponential spread is likely to re-emerge. It has been suggested that population-scale testing can help break the cycle of isolation and spread, but current detection methods are not capable of such large-scale processing. Here we propose LAMP-Seq, a barcoded Reverse-Transcription Loop-mediated Isothermal Amplification (RT-LAMP) protocol that could dramatically reduce the cost and complexity of population-scale testing. In this approach, individual samples are processed in a single heat step, producing barcoded amplicons that can be shipped to a sequencing center, pooled, and analyzed en masse. Using unique barcode combinations per sample from a compressed barcode space enables extensive pooling, significantly reducing cost and organizational efforts. Given the low cost and scalability of next-generation sequencing, we believe that this method can be affordably scaled to analyze millions of samples per day using existing sequencing infrastructure.

Footnotes

  • NOTE: This protocol has not been validated with clinical samples. To facilitate collaborations with interested parties to jointly advance the fight against the current coronavirus pandemic, we have set up a public forum on www.LAMP-Seq.org.

  • ↵13 Lead Contact

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 08, 2020.
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LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space
Jonathan L. Schmid-Burgk, David Li, David Feldman, Mikołaj Słabicki, Jacob Borrajo, Jonathan Strecker, Brian Cleary, Aviv Regev, Feng Zhang
bioRxiv 2020.04.06.025635; doi: https://doi.org/10.1101/2020.04.06.025635
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LAMP-Seq: Population-Scale COVID-19 Diagnostics Using a Compressed Barcode Space
Jonathan L. Schmid-Burgk, David Li, David Feldman, Mikołaj Słabicki, Jacob Borrajo, Jonathan Strecker, Brian Cleary, Aviv Regev, Feng Zhang
bioRxiv 2020.04.06.025635; doi: https://doi.org/10.1101/2020.04.06.025635

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