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Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing

[Image: see text] 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 inhib...

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Autores principales: Rozevsky, Yana, Gilboa, Tal, van Kooten, Xander F., Kobelt, Dennis, Huttner, Diana, Stein, Ulrike, Meller, Amit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510349/
https://www.ncbi.nlm.nih.gov/pubmed/32930583
http://dx.doi.org/10.1021/acsnano.0c06375
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author Rozevsky, Yana
Gilboa, Tal
van Kooten, Xander F.
Kobelt, Dennis
Huttner, Diana
Stein, Ulrike
Meller, Amit
author_facet Rozevsky, Yana
Gilboa, Tal
van Kooten, Xander F.
Kobelt, Dennis
Huttner, Diana
Stein, Ulrike
Meller, Amit
author_sort Rozevsky, Yana
collection PubMed
description [Image: see text] 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.
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spelling pubmed-75103492020-09-23 Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing Rozevsky, Yana Gilboa, Tal van Kooten, Xander F. Kobelt, Dennis Huttner, Diana Stein, Ulrike Meller, Amit ACS Nano [Image: see text] 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. American Chemical Society 2020-09-15 2020-10-27 /pmc/articles/PMC7510349/ /pubmed/32930583 http://dx.doi.org/10.1021/acsnano.0c06375 Text en This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Rozevsky, Yana
Gilboa, Tal
van Kooten, Xander F.
Kobelt, Dennis
Huttner, Diana
Stein, Ulrike
Meller, Amit
Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title_full Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title_fullStr Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title_full_unstemmed Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title_short Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing
title_sort quantification of mrna expression using single-molecule nanopore sensing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7510349/
https://www.ncbi.nlm.nih.gov/pubmed/32930583
http://dx.doi.org/10.1021/acsnano.0c06375
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