Model-guided design of RNA stabilizing elements for improved coronavirus diagnostics

Project: Research project

Project Details

Description

Model-guided design of RNA stabilizing elements for improved coronavirus diagnostics Model-guided design of RNA stabilizing elements for improved coronavirus diagnostics Model-guided design of RNA stabilizing elements for improved coronavirus diagnostics 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.
StatusActive
Effective start/end date9/17/219/16/25

Funding

  • HHS: National Institutes of Health (NIH): $1,763,188.00

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.