Evidence map›Paper›PMID 32577648›Full record

ArticlebioRxiv : the preprint server for biology2020

Highly multiplexed oligonucleotide probe-ligation testing enables efficient extraction-free SARS-CoV-2 detection and viral genotyping.

Joel J Credle, Matthew L Robinson, Jonathan Gunn, Daniel Monaco, Brandon Sie, Alexandra Tchir, Justin Hardick, Xuwen Zheng, Kathryn Shaw-Saliba, Richard E Rothman and 6 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 2 countries.

Joel J CredleInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Matthew L RobinsonDivision of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jonathan GunnInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Daniel MonacoInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Brandon SieInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Alexandra TchirInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Justin HardickDivision of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Xuwen ZhengInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Kathryn Shaw-SalibaDepartment of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Richard E RothmanDivision of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Susan H EshlemanDivision of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Andrew PekoszW. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Kasper HansenDepartment of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
Heba MostafaDivision of Medical Microbiology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Martin SteineggerBiological Sciences & Institute of Molecular Biology and Genetics, Seoul National University, Seoul, South Korea.
H Benjamin LarmanInstitute for Cell Engineering, Immunology Division, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
Johns Hopkins University · USSeoul National University · KR

Funding

LC: HIV Prevention Trials Network - Laboratory Support for the SARS-CoV-2 Seroprevalence Study (CoVPN 5002)UM1AI068613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SUSAN H ESHLEMAN, Mark A Marzinke · 2011 to 2026
$100.2M
HIV Prevention Trials Network: Network LaboratoryU01AI068613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI ESHLEMAN, SUSAN H · 2006 to 2010
$16.5M
NIH MARC USTAR program and The Transdisciplinary Biomolecular and Biomedical Sciences (TBBS) Program at FIU supplement: Mentor-mentee alliancesT34GM083688 · NIGMS · FLORIDA INTERNATIONAL UNIVERSITY · PI MILLS, DEETTA K · 2008 to 2023
$3.7M
A Highly Multiplexed Gene Expression Platform for Fixed Tissue SpecimensR21CA202875 · NCI · JOHNS HOPKINS UNIVERSITY · PI LARMAN, HARRY BENJAMIN · 2016 to 2018
$730k
NCI NIH HHS R21 CA202875NIAID NIH HHS HHSN272201400007CNIAID NIH HHS U01 AI068613NIAID NIH HHS UM1 AI068613NIGMS NIH HHS T34 GM083688
6 · The paper itself

Abstract

The emergence of SARS-CoV-2 has caused the current COVID-19 pandemic with catastrophic societal impact. Because many individuals shed virus for days before symptom onset, and many show mild or no symptoms, an emergent and unprecedented need exists for development and deployment of sensitive and high throughput molecular diagnostic tests. RNA-mediated oligonucleotide Annealing Selection and Ligation with next generation DNA sequencing (RASL-seq) is a highly multiplexed technology for targeted analysis of polyadenylated mRNA, which incorporates sample barcoding for massively parallel analyses. Here we present a more generalized method, capture RASL-seq ("cRASL-seq"), which enables analysis of any targeted pathogen- (and/or host-) associated RNA molecules. cRASL-seq enables highly sensitive (down to ~1-100 pfu/ml or cfu/ml) and highly multiplexed (up to ~10,000 target sequences) detection of pathogens. Importantly, cRASL-seq analysis of COVID-19 patient nasopharyngeal (NP) swab specimens does not involve nucleic acid extraction or reverse transcription, steps that have caused testing bottlenecks associated with other assays. Our simplified workflow additionally enables the direct and efficient genotyping of selected, informative SARS-CoV-2 polymorphisms across the entire genome, which can be used for enhanced characterization of transmission chains at population scale and detection of viral clades with higher or lower virulence. Given its extremely low per-sample cost, simple and automatable protocol and analytics, probe panel modularity, and massive scalability, we propose that cRASL-seq testing is a powerful new surveillance technology with the potential to help mitigate the current pandemic and prevent similar public health crises.

Identifiers

PMID32577648
PMCPMC7302202
OpenAlexW3033268003

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.