TY - JOUR
T1 - Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing
AU - Chappleboim, Alon
AU - Joseph-Strauss, Daphna
AU - Rahat, Ayelet
AU - Sharkia, Israa
AU - Adam, Miriam
AU - Kitsberg, Daniel
AU - Fialkoff, Gavriel
AU - Lotem, Matan
AU - Gershon, Omer
AU - Schmidtner, Anna Kristina
AU - Oiknine-Djian, Esther
AU - Klochendler, Agnes
AU - Sadeh, Ronen
AU - Dor, Yuval
AU - Wolf, Dana
AU - Habib, Naomi
AU - Friedman, Nir
N1 - Publisher Copyright:
© 2021 American Association for the Advancement of Science. All rights reserved.
PY - 2021/11/3
Y1 - 2021/11/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85121938986&partnerID=8YFLogxK
U2 - 10.1126/scitranslmed.abj2266
DO - 10.1126/scitranslmed.abj2266
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C2 - 34591660
AN - SCOPUS:85121938986
SN - 1946-6234
VL - 13
JO - Science Translational Medicine
JF - Science Translational Medicine
IS - 618
M1 - abj2266
ER -