Minimally instrumented SHERLOCK (miSHERLOCK) for CRISPR-based point-of-care diagnosis of SARS-CoV-2 and emerging variants
| Autor: | Nicole E. Weckman, Nina M. Donghia, James J. Collins, Xiao Tan, Helena de Puig, Geoffrey Lansberry, Angelo S. Mao, Carlos F. Ng, James B. Niemi, Devora Najjar, Peter Q. Nguyen, Nicolaas M. Angenent-Mari, Thomas C. Ferrante, Rose A. Lee, Audrey Ory, Hani M. Sallum, Luis R. Soekensen |
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| Rok vydání: | 2021 |
| Předmět: |
Multidisciplinary
Modality (human–computer interaction) Coronavirus disease 2019 (COVID-19) Computer science viruses Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fungi SciAdv r-articles Computational biology Treatment efficacy respiratory tract diseases body regions CRISPR Synthetic Biology Viral rna Health and Medicine skin and connective tissue diseases User needs Research Articles Research Article Point of care |
| Zdroj: | Science Advances |
| ISSN: | 2375-2548 |
| Popis: | An integrated, low-cost, sample-to-answer, CRISPR-based diagnostic detects SARS-CoV-2 and variants from unprocessed saliva. The COVID-19 pandemic highlights the need for diagnostics that can be rapidly adapted and deployed in a variety of settings. Several SARS-CoV-2 variants have shown worrisome effects on vaccine and treatment efficacy, but no current point-of-care (POC) testing modality allows their specific identification. We have developed miSHERLOCK, a low-cost, CRISPR-based POC diagnostic platform that takes unprocessed patient saliva; extracts, purifies, and concentrates viral RNA; performs amplification and detection reactions; and provides fluorescent visual output with only three user actions and 1 hour from sample input to answer out. miSHERLOCK achieves highly sensitive multiplexed detection of SARS-CoV-2 and mutations associated with variants B.1.1.7, B.1.351, and P.1. Our modular system enables easy exchange of assays to address diverse user needs and can be rapidly reconfigured to detect different viruses and variants of concern. An adjunctive smartphone application enables output quantification, automated interpretation, and the possibility of remote, distributed result reporting. |
| Databáze: | OpenAIRE |
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