Project Summary The coronavirus disease 2019 (COVID-19) – caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) – is a global pandemic with worldwide cases of over 35 million and a death toll of over 1 million people. In the United States, there are a total of over 7.5 million cases with over 210,000 deaths as of October 2020. The ability to identify COVID-19 infected patients rapidly, accurately, and cost-effectively is of paramount importance to control the disease outbreak. The two different types of COVID-19 tests are diagnostic tests and antibody tests. Specifically, the diagnostic tests can only identify active COVID-19 infected patients; the antibody tests can only indicate prior COVID-19 infections but not active cases. These diagnostic tests include quantitative reverse transcription polymerase chain reaction (qRT-PCR) and rapid antigen tests. In particular, the qRT-PCR is currently the most sensitive method (down to ~100 copies/mL) but can take >12 hours to perform and require trained personnel, specific reagents, and expensive machines. The rapid antigen tests provide results within 30 minutes, but these tests require the samples to contain high virus concentration (i.e., >107 virus particles/mL) leading to increasing chances of false-negative cases. In addition, one common example of the antibody tests is the enzyme-linked immunosorbent assay (ELISA). This test only applies to patients who have already developed the antibodies, which could take several days to weeks. Thus far, no single tests can detect both active and previously COVID-19 infected cases. The objective of the proposed research is to develop a proof-of-concept rapid and ultrasensitive virus-detection platform termed viral-ID, which is capable of simultaneous detecting the SARS-CoV-2 RNA and antibodies inside saliva for the identification of both active and previous COVID-19 infections within a single test. Specifically, the viral-ID platform will allow for specific molecular targeting, separation, enrichment, and filtering, all carried out within a single saliva droplet utilizing the nature-inspired coffee ring effect. Targeting and detection of the viral biomarkers will be carried out by aptamer-functionalized nanoparticles and deep-learning-enabled surface- enhanced Raman scattering (SERS), respectively. Using synthetic SARS-CoV-2 RNA and antibody-spiked saliva as a model system, the goal of this research is to demonstrate a bio-analysis platform capable of rapid sample preparation and ultrasensitive detection of both viral RNA (~10 – 100 copies/mL) and antibodies (~femtomolar) in a saliva droplet within 30 minutes. If successful, our viral-ID platform will provide all-in-one and best-in-class diagnostic and antibody test in terms of speed, sensitivity, and specificity for the rapid screening of COVID-19.

Project Narrative The coronavirus disease 2019 (COVID-19) is a global pandemic with worldwide cases of over 35 million and a death toll of over 1 million people. The goal of this proposed research is to demonstrate a bio-analysis platform capable of rapid sample preparation and ultrasensitive detection of both viral RNA (~10 – 100 copies/mL) and antibodies (~femtomolar) in a saliva droplet within 30 minutes. The successful implementation of the proposed platform will provide all-in-one and best-in-class diagnostic and antibody test in terms of speed, sensitivity, and specificity for the rapid screening of COVID-19.