Evidence map›Paper›PMID 32930583›Full record

ArticleACS nano2020

Quantification of mRNA Expression Using Single-Molecule Nanopore Sensing.

Yana Rozevsky, Tal Gilboa, Xander F van Kooten, Dennis Kobelt, Diana Huttner, Ulrike Stein, Amit Meller

Abstract read
In one paragraph

Article in ACS nano, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  5. Review
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  7. Probe-assisted detection of FeBiosensors & bioelectronics · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yana RozevskyDepartment of Biomedical Engineering, The Technion-IIT, Haifa 32000, Israel.
Tal GilboaDepartment of Biomedical Engineering, The Technion-IIT, Haifa 32000, Israel.
Xander F van KootenDepartment of Biomedical Engineering, The Technion-IIT, Haifa 32000, Israel.ORCID 0000-0003-2411-6174
Dennis KobeltExperimental and Clinical Research Center, Charité Universitätsmedizin, Berlin 10117, Germany.
Diana HuttnerDepartment of Biomedical Engineering, The Technion-IIT, Haifa 32000, Israel.
Ulrike SteinExperimental and Clinical Research Center, Charité Universitätsmedizin, Berlin 10117, Germany.
Amit MellerDepartment of Biomedical Engineering, The Technion-IIT, Haifa 32000, Israel.ORCID 0000-0001-7082-0985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

Indexed as

NanoporesBetacoronavirusBiosensing TechniquesHCT116 CellsHumansRNA, MessengerRNA, ViralS100 Calcium-Binding Protein A4SARS-CoV-2Single Molecule ImagingTrans-ActivatorsMACC1 protein, humanRNA, MessengerRNA, ViralS100A4 protein, humanS100 Calcium-Binding Protein A4Trans-ActivatorsMACC1mRNA expressionnanoporeS100A4SARS-CoV-2single-molecule counting

Identifiers

PMID32930583
PMCPMC7510349

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.