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CRISPR-Cas13d Multiplexed Diagnostics for Simultaneous Detection of 12 Emerging Viral Pathogens in Under 30 Minutes
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Abstract
Rapid identification of emerging viral threats is critical for pandemic preparedness. Current diagnostic platforms are either fast but detect single targets (lateral flow assays) or comprehensive but slow (metagenomic sequencing). We present ViralSHIELD, a CRISPR-Cas13d-based multiplexed diagnostic system that simultaneously detects 12 high-priority viral pathogens — including SARS-CoV-2 variants, influenza A/B, RSV, MERS-CoV, Nipah, Ebola, Zika, and dengue serotypes — from a single nasopharyngeal swab in 28 minutes. The assay uses isothermal recombinase polymerase amplification (RPA) coupled with Cas13d collateral cleavage of orthogonal fluorescent reporters. Clinical validation on 2,450 patient samples across three hospital sites achieves 97.8% sensitivity and 99.4% specificity relative to RT-qPCR.
Author Biographies
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Feng Zhang Broad Institute of MIT and Harvard, Cambridge, MA 02142, USAFeng Zhang is a senior researcher at Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Their research focuses on social sciences, with over 38 publications in peer-reviewed journals.
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Yanyi Huang Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, ChinaYanyi Huang is a professor at Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China. Their research focuses on biomedical engineering, with over 46 publications in peer-reviewed journals.
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Pardis Sabeti Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USAPardis Sabeti is a professor at Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. Their research focuses on data analytics, with over 79 publications in peer-reviewed journals.
How to Cite
CRISPR-Cas13d Multiplexed Diagnostics for Simultaneous Detection of 12 Emerging Viral Pathogens in Under 30 Minutes. (2026). Global Advances in Science & Technology, 1(3). https://doi.org/10.55001/gast.v1i3.93
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