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Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing

Bloom, Joshua S. and Jones, Eric M. and Gasperini, Molly and Lubock, Nathan B. and Sathe, Laila and Munugala, Chetan and Booeshaghi, A. Sina and Brandenberg, Oliver F. and Guo, Longhua and Boocock, James and Simpkins, Scott W. and Lin, Isabella and LaPierre, Nathan and Hong, Duke and Zhang, Yi and Oland, Gabriel and Choe, Bianca Judy and Chandrasekaran, Sukantha and Hilt, Evann E. and Butte, Manish J. and Damoiseaux, Robert and Cooper, Aaron R. and Yin, Yi and Pachter, Lior and Garner, Omai B. and Flint, Jonathan and Eskin, Eleazar and Luo, Chongyuan and Kosuri, Sriram and Kruglyak, Leonid and Arboleda, Valerie A. (2020) Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing. . (Unpublished)

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The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates of transmission by individuals who are asymptomatic at the time of transmission. Frequent, widespread testing of the asymptomatic population for SARS-CoV-2 is essential to suppress viral transmission and is a key element in safely reopening society. Despite increases in testing capacity, multiple challenges remain in deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests at the scale required for population screening of asymptomatic individuals. We have developed SwabSeq, a high-throughput testing platform for SARS-CoV-2 that uses next-generation sequencing as a readout. SwabSeq employs sample-specific molecular barcodes to enable thousands of samples to be combined and simultaneously analyzed for the presence or absence of SARS-CoV-2 in a single run. Importantly, SwabSeq incorporates an in vitro RNA standard that mimics the viral amplicon, but can be distinguished by sequencing. This standard allows for end-point rather than quantitative PCR, improves quantitation, reduces requirements for automation and sample-to-sample normalization, enables purification-free detection, and gives better ability to call true negatives. We show that SwabSeq can test nasal and oral specimens for SARS-CoV-2 with or without RNA extraction while maintaining analytical sensitivity better than or comparable to that of fluorescence-based RT-qPCR tests. SwabSeq is simple, sensitive, flexible, rapidly scalable, inexpensive enough to test widely and frequently, and can provide a turn around time of 12 to 24 hours.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemData/Code ItemData/Code
Bloom, Joshua S.0000-0002-7241-1648
Gasperini, Molly0000-0003-4559-8432
Lubock, Nathan B.0000-0001-8064-2465
Booeshaghi, A. Sina0000-0002-6442-4502
Brandenberg, Oliver F.0000-0001-5662-1234
Guo, Longhua0000-0001-9690-9750
Boocock, James0000-0003-0323-8818
Simpkins, Scott W.0000-0002-5997-2838
Butte, Manish J.0000-0002-4490-5595
Damoiseaux, Robert0000-0002-7611-7534
Cooper, Aaron R.0000-0003-4588-2513
Yin, Yi0000-0003-0963-2672
Pachter, Lior0000-0002-9164-6231
Garner, Omai B.0000-0002-7366-2692
Flint, Jonathan0000-0002-9427-4429
Eskin, Eleazar0000-0003-1149-4758
Luo, Chongyuan0000-0002-8541-0695
Kosuri, Sriram0000-0002-4661-0600
Kruglyak, Leonid0000-0002-8065-3057
Arboleda, Valerie A.0000-0002-9687-9122
Additional Information:The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. This version posted September 3, 2020. We thank the UCLA David Geffen School of Medicine's Dean's Office for their support, the Fast Grants, Inc for funding of this work. A generous donation was provided by Jane Semel. This work was supported by funding from the Howard Hughes Medical Institute (to LK) and DP5OD024579 (to VA). IL is supported by T32GM008042. Data Availability: Software and data are available at the shared github links. The core technology has been made available under the Open Covid Pledge, and software and data under the MIT license (UCLA) and Apache 2.0 license (Octant). Competing Interest Statement: E.M.J, M.G., N.B.L., S.W.S. and S.K. are employed by and hold equity, J.S.B. consults for and holds equity, and A.R.C holds equity in Octant Inc. which initially developed SwabSeq, and has filed for patents for some of the work here, though they have been made available under the Open Covid License: Author Declarations: I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes. The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All samples were obtained with UCLA IRB approval under studies IRB#20-000527 and IRB#20-001157. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes. I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes. I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes.
Funding AgencyGrant Number
Fast Grants, Inc.UNSPECIFIED
Howard Hughes Medical Institute (HHMI)UNSPECIFIED
NIH Predoctoral FellowshipT32GM008042
Record Number:CaltechAUTHORS:20201119-132151980
Persistent URL:
Official Citation:Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing. Joshua S. Bloom, Eric M. Jones, Molly Gasperini, Nathan B. Lubock, Laila Sathe, Chetan Munugala, A. Sina Booeshaghi, Oliver F. Brandenberg, Longhua Guo, James Boocock, Scott W. Simpkins, Isabella Lin, Nathan LaPierre, Duke Hong, Yi Zhang, Gabriel Oland, Bianca Judy Choe, Sukantha Chandrasekaran, Evann E. Hilt, Manish J. Butte, Robert Damoiseaux, Aaron R. Cooper, Yi Yin, Lior Pachter, Omai B. Garner, Jonathan Flint, Eleazar Eskin, Chongyuan Luo, Sriram Kosuri, Leonid Kruglyak, Valerie A. Arboleda. medRxiv 2020.08.04.20167874; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106738
Deposited By: Tony Diaz
Deposited On:19 Nov 2020 22:33
Last Modified:05 Jan 2021 19:20

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