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1. Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites

   https://doi.org/10.1128/spectrum.00797-22  

   Ham, Rachel E.; Smothers, Austin R.; Che, Rui; Sell, Keegan J.; Peng, Congyue Annie; Dean, Delphine (June 2022, Microbiology Spectrum)

   Mostafa, Heba H. (Ed.)

   ABSTRACT SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future. 

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2. Single-Particle Characterization of SARS-CoV-2 Isoelectric Point and Comparison to Variants of Interest

   https://doi.org/10.3390/microorganisms9081606  

   Areo, Oluwatoyin; Joshi, Pratik U.; Obrenovich, Mark; Tayahi, Moncef; Heldt, Caryn L. (August 2021, Microorganisms)

   SARS-CoV-2, the cause of COVID-19, is a new, highly pathogenic coronavirus, which is the third coronavirus to emerge in the past 2 decades and the first to become a global pandemic. The virus has demonstrated itself to be extremely transmissible and deadly. Recent data suggest that a targeted approach is key to mitigating infectivity. Due to the proliferation of cataloged protein and nucleic acid sequences in databases, the function of the nucleic acid, and genetic encoded proteins, we make predictions by simply aligning sequences and exploring their homology. Thus, similar amino acid sequences in a protein usually confer similar biochemical function, even from distal or unrelated organisms. To understand viral transmission and adhesion, it is key to elucidate the structural, surface, and functional properties of each viral protein. This is typically first modeled in highly pathogenic species by exploring folding, hydrophobicity, and isoelectric point (IEP). Recent evidence from viral RNA sequence modeling and protein crystals have been inadequate, which prevent full understanding of the IEP and other viral properties of SARS-CoV-2. We have thus experimentally determined the IEP of SARS-CoV-2. Our findings suggest that for enveloped viruses, such as SARS-CoV-2, estimates of IEP by the amino acid sequence alone may be unreliable. We compared the experimental IEP of SARS-CoV-2 to variants of interest (VOIs) using their amino acid sequence, thus providing a qualitative comparison of the IEP of VOIs. 

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3. LinearTurboFold: Linear-time global prediction of conserved structures for RNA homologs with applications to SARS-CoV-2

   https://doi.org/10.1073/pnas.2116269118  

   Li, Sizhen; Zhang, He; Zhang, Liang; Liu, Kaibo; Liu, Boxiang; Mathews, David H.; Huang, Liang (December 2021, Proceedings of the National Academy of Sciences)

   The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold’s purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 ′ and 3 ′ untranslated regions (UTRs) (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics. 

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4. Improving the specificity of nucleic acid detection with endonuclease-actuated degradation

   https://doi.org/10.1038/s42003-022-03242-x  

   Zou, Roger S.; Gavrilov, Momcilo; Liu, Yang; Rasoloson, Dominique; Conte, Madison; Hardick, Justin; Shen, Leo; Chen, Siqi; Pekosz, Andrew; Seydoux, Geraldine; et al (March 2022, Communications Biology)

   Abstract Nucleic acid detection is essential for numerous biomedical applications, but often requires complex protocols and/or suffers false-positive readouts. Here, we describe SENTINEL, an approach that combines isothermal amplification with a sequence-specific degradation method to detect nucleic acids with high sensitivity and sequence-specificity. Target single-stranded RNA or double-stranded DNA molecules are amplified by loop-mediated isothermal amplification (LAMP) and subsequently degraded by the combined action of lambda exonuclease and a sequence-specific DNA endonuclease (e.g., Cas9). By combining the sensitivity of LAMP with the precision of DNA endonucleases, the protocol achieves attomolar limits of detection while differentiating between sequences that differ by only one or two base pairs. The protocol requires less than an hour to complete using a 65 °C heat block and fluorometer, and detects SARS-CoV-2 virus particles in human saliva and nasopharyngeal swabs with high sensitivity. 

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5. Ultrasensitive Electrochemical Detection of Mutated Viral RNAs with Single-Nucleotide Resolution Using a Nanoporous Electrode Array (NPEA)

   https://doi.org/10.1021/acsnano.1c10824  

   Yoon, Jinho; Conley, Brian M.; Shin, Minkyu; Choi, Jin-Ha; Bektas, Cemile Kilic; Choi, Jeong-Woo; Lee, Ki-Bum (April 2022, ACS Nano)

   The detection of nucleic acids and their mutation derivatives is vital for biomedical science and applications. Although many nucleic acid biosensors have been developed, they often require pretreatment processes, such as target amplification and tagging probes to nucleic acids. Moreover, current biosensors typically cannot detect sequence-specific mutations in the targeted nucleic acids. To address the above problems, herein, we developed an electrochemical nanobiosensing system using a phenomenon comprising metal ion intercalation into the targeted mismatched double-stranded nucleic acids and a homogeneous Au nanoporous electrode array (Au NPEA) to obtain (i) sensitive detection of viral RNA without conventional tagging and amplifying processes, (ii) determination of viral mutation occurrence in a simple detection manner, and (iii) multiplexed detection of several RNA targets simultaneously. As a proof-of-concept demonstration, a SARS-CoV-2 viral RNA and its mutation derivative were used in this study. Our developed nanobiosensor exhibited highly sensitive detection of SARS-CoV-2 RNA (∼1 fM detection limit) without tagging and amplifying steps. In addition, a single point mutation of SARS-CoV-2 RNA was detected in a one-step analysis. Furthermore, multiplexed detection of several SARS-CoV-2 RNAs was successfully demonstrated using a single chip with four combinatorial NPEAs generated by a 3D printing technique. Collectively, our developed nanobiosensor provides a promising platform technology capable of detecting various nucleic acids and their mutation derivatives in highly sensitive, simple, and time-effective manners for point-of-care biosensing. 

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