Dataset on optimization and development of a point-of-care glucometer-based SARS-CoV-2 detection assay using aptamers

Data in Brief

Drew A. Hall¹  Naveen K. Singh²  Sydney C. Morgan³  Celestine Magallanes³  Louise C. Laurent³  Aaron F. Carlin⁴  Eliah S. Aronoff-Spencer⁴  Partha Ray⁵ 

[1] Corresponding author at: Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California – San Diego, La Jolla, CA 92093, USA.;Department of Electrical and Computer Engineering, University of California – San Diego, La Jolla, CA 92093, USA;Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California – San Diego, La Jolla, CA 92093, USA;Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California – San Diego, La Jolla, CA 92093, USA;Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California – San Diego Health, La Jolla, CA 92093, USA;

关键词: Aptamer;    Enzyme;    Glucometer;    SARS-CoV-2;    COVID-19;    Point-of-care;   

DOI  :  

来源: DOAJ

【 摘 要 】

We present supplementary data for the published article, “Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer” [1]. The assay described is designed to be performed at home or in a clinic without expensive instrumentation or professional training. SARS-CoV-2 is detected by an aptamer-based assay that targets the Nucleocapsid (N) or Spike (S) antigens. Binding of the N or S protein to their respective aptamer results in the competitive release of a complementary antisense-invertase enzyme complex. The released enzyme then catalyzes the conversion of sucrose to glucose that is measured by an off-the-shelf glucometer. The data presented here describe the optimization of the assay parameters and their contribution to developing this aptamer-based assay to detect SARS-CoV-2. The assay performance was checked in a standard buffer, contrived samples, and patient samples validated with well-established scientific methods. The resulting dataset can be used to further develop glucometer-based assays for diagnosing other communicable and non-communicable diseases.

【 授权许可】

Unknown