Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows.
JMG, COVID-19, DNA Primers, Genome, Viral, Humans, Quality Control, RNA, Viral, Reproducibility of Results, SARS-CoV-2, Sequence Analysis, Whole Genome Sequencing, Workflow
Nat Microbiol 2022 Jan; 7(1):108-119
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.
Lagerborg, Kim A; Normandin, Erica; Bauer, Matthew R; Adams, Gordon; Figueroa, Katherine; Loreth, Christine; Gladden-Young, Adrianne; Shaw, Bennett M; Pearlman, Leah R; Berenzy, Daniel; Dewey, Hannah B; Kales, Susan; Dobbins, Sabrina T; Shenoy, Erica S; Hooper, David; Pierce, Virginia M; Zachary, Kimon C; Park, Daniel J; MacInnis, Bronwyn L; Tewhey, Ryan; Lemieux, Jacob E; Sabeti, Pardis C; Reilly, Steven K; and Siddle, Katherine J, "Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows." (2022). Faculty Research 2022. 8.