Project Summary
Fast, inexpensive, and sensitive methods to detect the SARS-CoV-2 coronavirus are instrumental
in containing the spread of COVID-19. Currently, nucleic acid testing of respiratory samples using
RT-PCR is the primary and most commonly used method for diagnosing patients in the acute
phase of the infection. However, this standard approach suffers from the need for special
equipment and well-trained personnel and hence has become a bottleneck to meet the urgent
demand for large-scale screening. A range of new RNA-based technologies, including toehold
switches and CRISPR/Cas systems, are being actively developed with the aim to implement
diagnostic tests that are ultra-sensitive, easy to deploy, and make use of enzymes and reagents
separate from the traditional PCR pipeline. One common and critical component of these methods
is the engineering of RNA molecules to detect target viral sequences. Consequently, their
performance in terms of specificity and sensitivity have been significantly hindered by the fast
degradation of RNAs caused by the RNases ubiquitous in both clinical sample matrices and as
byproducts of biomolecular reagent production.
Here we propose to enhance coronavirus diagnostic performance by programming RNase
resistance into assay components, in turn increasing RNA stability and enhancing test
sensitivity and speed. We will rationally design RNA 5’ UTR sequences and the resulting
secondary structures of mRNA, toehold switch RNA, and CRISPR guide RNAs to modulate
their resistance to RNase activities and hence quantitatively tune their stability. Results
from the proposed forward engineering studies will increase our understanding and control of
RNA dynamics and provide a widely applicable strategy to improve coronavirus detection
efficiencies of many technologies under development. Impact: A comprehensively studied RNA
design scheme to improve RNA stability will be complementary to current technologies under
development to give them a boost in performance, and provide underlying design strategies with
potential broader applicability, such as overcoming the stability barrier for mRNA-based vaccines.
There are three specific aims in this proposal: Aim 1: Characterize and model the role of 5’
secondary structures in fine-tuning mRNA stability; Aim 2: Optimize sensing RNAs for detection
of COVID-19; Aim 3: Use dtRNAs to enhance sample and amplified RNA stability for improved
diagnostics.