A team of researchers at MIT has developed a molecular assay to detect sub-picomolar levels of the SARS-CoV-2’s spike protein receptor-binding domain (S-RBD) using computationally validated peptide beacons in a single-step detection through the production of a fluorescence signal. The team has released their findings on the bioRxiv* preprint server.
The most widely employed diagnostic tests for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agents of coronavirus disease 2019 (COVID-19), are the reverse transcription-polymerase chain reaction (RT-PCR)-based methods - with limits of detection (LoD) of 102 -103 RNA copies/ml, which is about 1-10 attomolar (aM) RNA in the test volume.
However, RT-PCR tests are laborious, requiring expensive nucleic acid isolation, purification, and processing steps. This increases both the turnaround time of detection and the cost of testing. While other technologies based on CRISPR and loop-mediated amplification for diagnostics exist, rapid point-of-care diagnostics for detecting SARS-CoV-2 can accelerate the fight to control the outbreaks of the infection.
In a recent study, researchers from the Massachusetts Institute of Technology (MIT) have engineered molecular beacons, using deep-learning protein design, that light up at highly sensitive sub-picomolar concentrations of the SARS-CoV-2 RBD (receptor-binding domain). The beacon functions as a conformational switch: goes ON in the presence of the viral RBD by producing a fluorescence signal utilizing a fluorophore-quencher pair.
The beacons form a heterodimer containing two peptides together, with a binding ligand between them to detect the presence of S-RBD.
In the absence of S-RBD (OFF), the peptide beacons adopt a closed conformation that opens when bound to the S-RBD, and the fluorophore-quencher pair at the two ends of the heterodimer stems produces a fluorescence signal (ON).
The researchers demonstrated that two candidate beacons, C17LC21 and C21LC21, can detect the RBD with limits of detection (LoD) in the sub-picomolar range.
Our eventual goal is to integrate these optimized beacons within miniaturized total internal reflection fluorescence (TIRF) microscopes, which provide exquisite sensitivity by exciting fluorophores present within nanometer proximity of the device surface, producing high signal-to-background ratios and enabling rapid and ultra-sensitive detection of SARS-CoV-2,” said the researchers.
Here, the researchers have used the mechanism of Forster Resonance Energy Transfer (FRET), where the efficiency of energy transfer between the fluorophore and quencher is proportional to their spatial distance. The presence or absence of the S-RBD causes a small change in the spatial distance between the two beacon arms, drastically changing the FRET efficiency.
Thus, this affects the fluorescent quantum yield of the fluorophore. The increase in the fluorescence signal is proportional to the amount of the S-RBD present. The researchers have used the commonly-used fluorophore-quencher pair: fluorescein isothiocyanate (FITC) and [4-(N,N-dimethylamino)phenylazo] benzoyl (DABCYL), respectively.
The researchers computationally selected the peptide beacon candidates (C13LC21, C17LC21, and C21L21) that successfully docked the S-RBD separating the two beacon arms that house the fluorophore and the quencher, switching to the ON conformation.
After this confirmation, they experimentally tested these three peptide beacon designs for binding capability with S-RBD in human cells and for detection response in vitro. They observed that the C17LC21 showed the highest sensitivity towards S-RBD with an LoD of nearly 20 fM (Kd = 1.615 × 10−12), followed by C21LC21 having an LoD of 400 fM (Kd = 6.766 × 10−13).
They concluded that the C17LC21 and C21LC21 could detect the presence of S-RBD with sub-picomolar sensitivity and low cross-reactivity. Thus motivating the application of these molecular beacons for rapid detection of SARS-CoV-2.
This work “showcases a use case for current deep learning tools for protein structure prediction in a protein design pipeline,” said the researchers. They demonstrated this by employing a hybrid approach of state-of-the-art protein modeling tools for the molecular beacon design. Followed with robust experimental validation, this molecular beacon design serves as a powerful platform to fight COVID-19 and future emerging viral threats.
The researchers write:
In this study, using existing deep learning tools for protein structure prediction and energy-based modeling suites, we designed and tested a set of molecular beacons that can potently bind to the S-RBD and release a fluorescence signal via FRET, enabling sub-picomolar detection levels.”
Integration of these peptide beacons within optical sensors, such as miniature TIRF microscopes, may reduce the LoD to sub-femtomolar level, thus yielding a rapid, point-of-care diagnostic platform for SARS-CoV-2, the researchers envision.
bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.