PT  - JOURNAL ARTICLE
AU  - Hayden C. Metsky
AU  - Catherine A. Freije
AU  - Tinna-Solveig F. Kosoko-Thoroddsen
AU  - Pardis C. Sabeti
AU  - Cameron Myhrvold
TI  - CRISPR-based surveillance for COVID-19 using genomically-comprehensive machine learning design
AID  - 10.1101/2020.02.26.967026
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.02.26.967026
4099  - http://biorxiv.org/content/early/2020/03/02/2020.02.26.967026.1.short
4100  - http://biorxiv.org/content/early/2020/03/02/2020.02.26.967026.1.full
AB  - The emergence and outbreak of SARS-CoV-2, the causative agent of COVID-19, has rapidly become a global concern and has highlighted the need for fast, sensitive, and specific tools to surveil circulating viruses. Here we provide assay designs and experimental resources, for use with CRISPR-based nucleic acid detection, that could be valuable for ongoing surveillance. We provide assay designs for detection of 67 viral species and subspecies, including: SARS-CoV-2, phylogenetically-related viruses, and viruses with similar clinical presentation. The designs are outputs of algorithms that we are developing for rapidly designing nucleic acid detection assays that are comprehensive across genomic diversity and predicted to be highly sensitive and specific. Of our design set, we experimentally screened 4 SARS-CoV-2 designs with a CRISPR-Cas13 detection system and then extensively tested the highest-performing SARS-CoV-2 assay. We demonstrate the sensitivity and speed of this assay using synthetic targets with fluorescent and lateral flow detection. Moreover, our provided protocol can be extended for testing the other 66 provided designs. Assay designs are available at https://adapt.sabetilab.org/.