Purely electrical SARS-CoV-2 sensing based on single-molecule counting.

The majority of RNA based COVID-19 diagnostics employ enzymatic amplification to achieve high sensitivity, but this relies on arbitrary thresholding, which complicates the comparison of test results and may lead to false outcomes. Here we introduce solid-state nanopore sensing for label-free quantification of SARS-CoV-2 RNA in clinical nasal swab samples. This PCR-free method involves reverse transcribing a target gene on the viral RNA before enzymatically digesting all but the resulting dsDNA. Ratiometric quantification of RNA abundance is achieved by single-molecule counting and length-based nanopore identification of dsDNA from a SARS-CoV-2 gene and a human reference gene. We graded nasal swab samples from >15 subjects and find that the SARS-CoV-2 ratiometric nanopore index correlates well with the reported RT-qPCR threshold cycle for positive classified samples. Remarkably, nanopore analysis also reports quantitative positive outcomes for clinical samples classified as negative by RT-qPCR, suggesting that the method may be used to diagnose COVID-19 in samples that may evade detection. We show that the sample preparation workflow can be implemented using a compact microfluidic device with integrated thermal control for semi-automated processing of extremely small sample volumes, offering a viable route towards automated, fast and affordable RNA quantification in a small and portable device.

Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing.

RNA quantification methods are broadly used in life science research and in clinical diagnostics. Currently, real-time reverse transcription polymerase chain reaction (RT-qPCR) is the most common analytical tool for RNA quantification. However, in cases of rare transcripts or inhibiting contaminants in the sample, an extensive amplification could bias the copy number estimation, leading to quantification errors and false diagnosis. Single-molecule techniques may bypass amplification but commonly rely on fluorescence detection and probe hybridization, which introduces noise and limits multiplexing. Here, we introduce reverse transcription quantitative nanopore sensing (RT-qNP), an RNA quantification method that involves synthesis and single-molecule detection of gene-specific cDNAs without the need for purification or amplification. RT-qNP allows us to accurately quantify the relative expression of metastasis-associated genes MACC1 and S100A4 in nonmetastasizing and metastasizing human cell lines, even at levels for which RT-qPCR quantification produces uncertain results. We further demonstrate the versatility of the method by adapting it to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA against a human reference gene. This internal reference circumvents the need for producing a calibration curve for each measurement, an imminent requirement in RT-qPCR experiments. In summary, we describe a general method to process complicated biological samples with minimal losses, adequate for direct nanopore sensing. Thus, harnessing the sensitivity of label-free single-molecule counting, RT-qNP can potentially detect minute expression levels of RNA biomarkers or viral infection in the early stages of disease and provide accurate amplification-free quantification.