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Amplification-Free COVID-19 Detection by Digital Droplet REVEALR.
Yang, Kefan; Chaput, John C.
  • Yang K; Department of Chemical and Biomolecular Engineering, University of California, Irvine, California 92697-3958, United States.
  • Chaput JC; Department of Pharmaceutical Sciences, University of California, Irvine, California 92697-3958, United States.
ACS Synth Biol ; 12(4): 1331-1338, 2023 04 21.
Article in English | MEDLINE | ID: covidwho-2287537
ABSTRACT
The COVID-19 pandemic, caused by the SARS-CoV-2 virus, exposed a pressing need for new public health tools for pathogen detection, disease diagnosis, and viral genotyping. REVEALR (RNA-encoded viral nucleic acid analyte reporter) is an isothermal DNAzyme-based point-of-care diagnostic that functions with a detection limit of ∼10 copies/µL when coupled with a preamplification step and can be utilized for viral genotyping of SARS-CoV-2 variants of concern through base pair mismatch recognition in a competitive binding format. Here, we describe an advanced REVEALR platform, termed digital droplet REVEALR (ddREVEALR), that can achieve direct viral detection and absolute sample quantitation utilizing a signal amplification strategy that relies on chemical modifications, DNAzyme multiplexing, and volume compression. Using an AI-assisted image-based readout, ddREVEALR was found to achieve 95% positive predictive agreement from a set of 20 nasal pharyngeal swabs collected at UCI Medical Center in Orange, California. We propose that the combination of amplification-free and protein-free analysis makes ddREVEALR a promising application for direct viral RNA detection of clinical samples.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: DNA, Catalytic / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: ACS Synth Biol Year: 2023 Document Type: Article Affiliation country: Acssynbio.3c00105

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Full text: Available Collection: International databases Database: MEDLINE Main subject: DNA, Catalytic / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: ACS Synth Biol Year: 2023 Document Type: Article Affiliation country: Acssynbio.3c00105