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| Item Type: | Article |
|---|---|
| Title: | Quantification of mRNA expression using single-molecule nanopore sensing |
| Creators Name: | Rozevsky, Y., Gilboa, T., van Kooten, X.F., Kobelt, D., Huttner, D., Stein, U. and Meller, A. |
| Abstract: | 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 non-metastasizing 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. |
| Keywords: | Nanopore, Single-Molecule Counting, mRNA Expression, SARS-CoV-2, MACC1, S100A4 |
| Source: | ACS Nano |
| ISSN: | 1936-0851 |
| Publisher: | American Chemical Society |
| Volume: | 14 |
| Number: | 10 |
| Page Range: | 13964-13974 |
| Date: | 27 October 2020 |
| Official Publication: | https://doi.org/10.1021/acsnano.0c06375 |
| PubMed: | View item in PubMed |
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