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Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing.
Chappleboim, Alon; Joseph-Strauss, Daphna; Rahat, Ayelet; Sharkia, Israa; Adam, Miriam; Kitsberg, Daniel; Fialkoff, Gavriel; Lotem, Matan; Gershon, Omer; Schmidtner, Anna-Kristina; Oiknine-Djian, Esther; Klochendler, Agnes; Sadeh, Ronen; Dor, Yuval; Wolf, Dana; Habib, Naomi; Friedman, Nir.
  • Chappleboim A; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Joseph-Strauss D; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Rahat A; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Sharkia I; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Adam M; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Kitsberg D; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Fialkoff G; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Lotem M; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Gershon O; Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Schmidtner AK; Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Oiknine-Djian E; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Klochendler A; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Sadeh R; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Dor Y; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Wolf D; Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Habib N; Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Friedman N; Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
Sci Transl Med ; 13(618): eabj2266, 2021 Nov 03.
Article in English | MEDLINE | ID: covidwho-1443348
ABSTRACT
Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests have relied on RNA extraction followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays. Whereas automation improved logistics and different pooling strategies increased testing capacity, highly multiplexed next-generation sequencing (NGS) diagnostics remain a largely untapped resource. NGS tests have the potential to markedly increase throughput while providing crucial SARS-CoV-2 variant information. Current NGS-based detection and genotyping assays for SARS-CoV-2 are costly, mostly due to parallel sample processing through multiple steps. Here, we have established ApharSeq, in which samples are barcoded in the lysis buffer and pooled before reverse transcription. We validated this assay by applying ApharSeq to more than 500 clinical samples from the Clinical Virology Laboratory at Hadassah hospital in a robotic workflow. The assay was linear across five orders of magnitude, and the limit of detection was Ct 33 (~1000 copies/ml, 95% sensitivity) with >99.5% specificity. ApharSeq provided targeted high-confidence genotype information due to unique molecular identifiers incorporated into this method. Because of early pooling, we were able to estimate a 10- to 100-fold reduction in labor, automated liquid handling, and reagent requirements in high-throughput settings compared to current testing methods. The protocol can be tailored to assay other host or pathogen RNA targets simultaneously. These results suggest that ApharSeq can be a promising tool for current and future mass diagnostic challenges.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: Sci Transl Med Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Scitranslmed.abj2266

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: Sci Transl Med Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Scitranslmed.abj2266