PT  - JOURNAL ARTICLE
AU  - Hayden C. Metsky
AU  - Nicole L. Welch
AU  - Priya P. Pillai
AU  - Nicholas J. Haradhvala
AU  - Laurie Rumker
AU  - Sreekar Mantena
AU  - Yibin B. Zhang
AU  - David K. Yang
AU  - Cheri M. Ackerman
AU  - Juliane Weller
AU  - Paul C. Blainey
AU  - Cameron Myhrvold
AU  - Michael Mitzenmacher
AU  - Pardis C. Sabeti
TI  - Designing viral diagnostics with model-based optimization
AID  - 10.1101/2020.11.28.401877
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2020.11.28.401877
4099  - http://biorxiv.org/content/early/2021/09/28/2020.11.28.401877.short
4100  - http://biorxiv.org/content/early/2021/09/28/2020.11.28.401877.full
AB  - Diagnostics, particularly for rapidly evolving viruses, stand to benefit from a principled, measurement-driven design that harnesses machine learning and vast genomic data—yet the capability for such design has not been previously built. Here, we develop and extensively validate an approach to designing viral diagnostics that applies a learned model within a combinatorial optimization framework. Concentrating on CRISPR-based diagnostics, we screen a library of 19,209 diagnostic–target pairs and train a deep neural network that predicts, from RNA sequence alone, diagnostic signal better than contemporary techniques. Our model then makes it possible to design assays that are maximally sensitive over the spectrum of a virus’s genomic variation. We introduce ADAPT (https://adapt.guide), a system for fully-automated design, and use ADAPT to design optimal diagnostics for the 1,933 vertebrate-infecting viral species within 2 hours for most species and 24 hours for all but 3. We experimentally show ADAPT’s designs are sensitive and specific down to the lineage level, including against viruses that pose challenges involving genomic variation and specificity. ADAPT’s designs exhibit significantly higher fluorescence and permit lower limits of detection, across a virus’s entire variation, than the outputs of standard design techniques. Our model-based optimization strategy has applications broadly to viral nucleic acid diagnostics and other sequence-based technologies, and, paired with clinical validation, could enable a critically-needed, proactive resource of assays for surveilling and responding to pathogens.Competing Interest StatementH.C.M., N.J.H., C.M., and P.C.S. are co-inventors on a patent application filed by the Broad Institute related to work in this manuscript. N.J.H. is a consultant to Constellation Pharmaceuticals. P.C.B. is a consultant to and equity holder in 10X Genomics, GALT, Celsius Therapeutics, and Next Generation Diagnostics. P.C.S. is a co-founder of and consultant to Sherlock Biosciences and a Board Member of Danaher Corporation, and holds equity in the companies.