Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows

合成DNA插入片段(SDSI)能够实现SARS-CoV-2测序工作流程中的样本追踪和样本间污染检测。

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作者:Kim A Lagerborg # ,Erica Normandin # ,Matthew R Bauer # ,Gordon Adams ,Katherine Figueroa ,Christine Loreth ,Adrianne Gladden-Young ,Bennett M Shaw ,Leah R Pearlman ,Daniel Berenzy ,Hannah B Dewey ,Susan Kales ,Sabrina T Dobbins ,Erica S Shenoy ,David Hooper ,Virginia M Pierce ,Kimon C Zachary ,Daniel J Park ,Bronwyn L MacInnis ,Ryan Tewhey ,Jacob E Lemieux ,Pardis C Sabeti ,Steven K Reilly ,Katherine J Siddle

Abstract

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.

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