Study Information

dbGaP Study Accession: phs002700

NIH Institute/Center: NIAAA

RADx Data Program: RADx-rad

DOI: 10.60773/kt6c-e369

Release Date: 07/27/2022

Study Description: Coronavirus 2019 (COVID-19) has afflicted 6.2 million Americans and killed 190,000 as of early September 2020 (WHO website); a roughly 3% mortality. Between a shortage in testing and unidentified asymptomatic individuals, the actual number of those infected could be 6 to 24-fold higher than that reported. SARS-CoV-2 (CoV-2), the virus underlying the disease, results in a range of symptoms; in select cases a severe respiratory illness that impedes breathing could lead to hospitalization and death. CoV-2 is transmitted person-to-person via inhalation of the virus through mucosal membranes of the nose and throat from transfer after touching a contaminated surface or by inhaling aerosolized virus. Unfortunately, COVID-19 was likely to be prevalent well into 2021 and beyond. The ability to test for CoV-2 must be increased. First, testing is needed to diagnose individuals that are symptomatic or asymptomatic to reduce community spread. And second, monitoring gathering areas for airborne virus that could inform the decision to shutdown a space or implement disinfection and mitigation of an area. This study examined an electrochemical biosensor in two detection devices, 1) a diagnostic breathalyzer for instant detection of CoV-2 and 2) an airborne detector for real-time, continuous surveillance of a large space. A novel ultra-sensitive, antibody-based electrochemical biosensor to detect CoV-2 repeat binding domain (RBD) spike protein was developed. The technology was based on a micro-immunoelectrode (MIE) biosensor pioneered by the Cirrito laboratory to study protein dynamics in the setting of neurodegeneration. The biosensor used voltammetry to measure the oxidation of tyrosine amino acids; oxidation was the release of electrons that the biosensor measures as a change in current. Antibodies were covalently attached to the electrode surface to provide selectivity. This prototype CoV-2 biosensor was sensitive to 2 femtogram/ml, compared to several current CoV-2 antigen tests that are sensitive to the low picogram/ml range. The proposal (Aim 1) optimized the CoV-2 biosensor to detect CoV-2 viral particles, as well as test several parameters to increase sensitivity and longevity. In Aim 2, a test breathalyzer was built that will utilize a nebulizer to generate virus laden air containing aerosol droplets similar to a breath that contain defined concentrations of CoV-2 viral particles. Aim 3 tested the airborne biosensor in a realistic environment. Co-I Chakrabarty's laboratory had unique capabilities of mimicking real-world environmental conditions, especially in the context of atmospheric aerosols, necessary for testing and optimizing the biosensor's performance for field deployment. Atmospheric conditions included relative humidity (RH) and temperature, as well as common airborne pollutants found indoors. Finding novel means to detect the CoV-2, as well as create a platform to detect other and future pathogens, which would enable the ability to limit the viral spread throughout the community in the current and future pandemics.

Updated Date: 05/16/2023

Principal Investigator: Cirrito, John R

Has Data Files: Yes

Study Domain: Medical Device/Tool Development; Novel Biosensing and VOC; Biosensor Technology

Data Collection Method: Breath Analysis Device / Airborne Detection Device

Keywords: Screen-Printed Electrode; Nanobody; Electrochemistry; Electrochemical Biosensor; Airborne Biosensor

Study Design: Device Verification Study

Multi-Center Study: FALSE

Data Types: Other; Immunological

Data Types, Other: Assessing viral concentration in solution and aerosolized samples

Study Start Date: 12/21/2020

Study End Date: 11/30/2022

Species: Non-Human Data

Estimated Cohort Size: 24

Study Population Focus: N/A

Publication URL: https://pubmed.ncbi.nlm.nih.gov/37498298/; https://pubmed.ncbi.nlm.nih.gov/37429842/

Acknowledgement Statement: This study was supported through funding, 3U01AA029331-02S1, for the National Institute on Alcohol Abuse and Alcoholism (NIAAA) as part of the RADx-rad program. Work was performed in collaboration with Dr. Rajan Chakrabarty and Carla Yuede at Washington University. Approved users should acknowledge the provision of data access by dbGaP for accession phs002700.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.

Funding Opportunity Announcement (FOA) Number: PA-20-272

NIH Grant or Contract Number(s): 3U01AA029331-02S1

Consent/Data Use Limitations: General Research Use

Data Files
Total Files: 7
Data Files: 5
Metadata Files: 1
Dictionary Files: 1
Study Datasets Table
File Name
File Type
File Format(s)
# of Records
# of Variables
Metadata
Dictionary
rad_014_331-01_DATA_WUSTL1_TESTRESULTS_DATA_origcopy.csvTabular Data - Non-harmonizedcsv1004

rad_014_331-01_DATA_WUSTL1_CLINICALSAMPLES_DATA_origcopy.csvTabular Data - Non-harmonizedcsv981

rad_014_331-01_WUSTL1_DATA_transformcopy.csvTabular Data - Harmonizedcsv9

rad_014_331-01_DATA_WUSTL1_PERFORMANCERESULTS_DATA_origcopy.csvTabular Data - Non-harmonizedcsv997

rad_014_331-01_WUSTL1_DATA_origcopy.csvTabular Data - Non-harmonizedcsv9