# Rapid SARS-CoV-2 Detection Using Amplicon Templated Reporter Enzyme Assembly

> **NIH NIH R03** · STATE UNIVERSITY OF NY,BINGHAMTON · 2022 · $78,500

## Abstract

ABSTRACT
We are proposing to pilot test a new enzyme biosensor technology for the purpose of enhancing
isothermal RNA amplification assays for SARS-CoV-2. Our overarching goal is to validate this
technology, called DETECT, as biomolecular tool to increase the sensitivity, specificity, and
speed of SARS-CoV-2 testing. DETECT is based on a modified split luciferase enzyme
complementation assay. Instead of the standard bait and prey fused protein constructs, we
connect two non-interacting luciferase fragments to SARS-CoV-2 oligonucleotide probes.
Conjugation of the luciferase fragments to the oligonucleotides uses a chemi-enzymatic method
developed in the investigator's lab. The oligonucleotides are designed to anneal to adjacent
segments in a unique SARS-CoV-2 amplicon. With samples containing the amplicon, the split
luciferase fragments are brought together through base pairing of their attached
oligonucleotides with the SARS-CoV-2 amplicon. Molecular assembly reconstitutes functional
luciferase from the two fragments, enabling robust light output. In preliminary experiments, we
validate the central and novel concept of DETECT: protein fragment complementation via
nucleic acid base pairing. In controls where base pairing of the oligonucleotides is blocked,
either by exonuclease pretreatment or by competitor oligonucleotide, we observe luminescence
readings on par with buffer only samples. By contrast, in experimental samples where
oligonucleotide base pairing is supported, we observe luciferase signal that is increased 100-
fold over background. These preliminary experiments were carried out with the split luciferase-
oligonucleotide conjugates at 25 nM. Over the course of this 2-year project, we propose to
evaluate the DETECT system quantitatively for specificity, sensitivity and speed, thereby
assessing the clinical potential of this biosensor technology. Although our objective here is
diagnosing SARS-CoV-2 infection, the DETECT system is easily re-programmed by changing
the oligonucleotide probe sequences. Thus DETECT holds promise as a new and innovative
diagnostic platform.

## Key facts

- **NIH application ID:** 10438883
- **Project number:** 5R03AI163907-02
- **Recipient organization:** STATE UNIVERSITY OF NY,BINGHAMTON
- **Principal Investigator:** Brian Patrick Callahan
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $78,500
- **Award type:** 5
- **Project period:** 2021-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10438883

## Citation

> US National Institutes of Health, RePORTER application 10438883, Rapid SARS-CoV-2 Detection Using Amplicon Templated Reporter Enzyme Assembly (5R03AI163907-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10438883. Licensed CC0.

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