Evidence map›Paper›PMID 35532013›Full record

ArticleeLife2022

A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva.

Robert Warneford-Thomson, Parisha P Shah, Patrick Lundgren, Jonathan Lerner, Jason Morgan, Antonio Davila, Benjamin S Abella, Kenneth Zaret, Jonathan Schug, Rajan Jain and 2 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
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

12 authors at 1 institution in 1 country.

Robert Warneford-ThomsonGraduate Group in Biochemistry and Biophysics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0002-4521-0568
Parisha P ShahEpigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0002-7756-6868
Patrick LundgrenDepartment of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0003-1014-8941
Jonathan LernerDepartment of Cell and Developmental Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Jason MorganDepartment of Emergency Medicine and Penn Acute Research Collaboration, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Antonio DavilaDepartment of Emergency Medicine and Penn Acute Research Collaboration, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Benjamin S AbellaDepartment of Emergency Medicine and Penn Acute Research Collaboration, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Kenneth ZaretEpigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Jonathan SchugNext-Generation Sequencing Core, Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Rajan JainEpigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0002-1979-044X
Christoph A ThaissDepartment of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Roberto BonasioEpigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.ORCID 0000-0002-0767-0889
University of Pennsylvania · US

Funding

Deciphering Nuclear Lamina-Chromatin Organization in Cellular Competence and Cardiac DevelopmentDP2HL147123 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI JAIN, RAJAN · 2018 to 2018
$2.4M
NHLBI NIH HHS DP2 HL147123
6 · The paper itself

Abstract

The COVID-19 pandemic has created an urgent need for rapid, effective, and low-cost SARS-CoV-2 diagnostic testing. Here, we describe COV-ID, an approach that combines RT-LAMP with deep sequencing to detect SARS-CoV-2 in unprocessed human saliva with a low limit of detection (5-10 virions). Based on a multi-dimensional barcoding strategy, COV-ID can be used to test thousands of samples overnight in a single sequencing run with limited labor and laboratory equipment. The sequencing-based readout allows COV-ID to detect multiple amplicons simultaneously, including key controls such as host transcripts and artificial spike-ins, as well as multiple pathogens. Here, we demonstrate this flexibility by simultaneous detection of 4 amplicons in contrived saliva samples: SARS-CoV-2, influenza A, human

Indexed as

COVID-19OrthomyxoviridaeHumansPandemicsRNA, ViralSalivaSARS-CoV-2Sensitivity and SpecificityRNA, ViralCOVIDhumaninfectious diseasemicrobiologyRT-LAMPsequencingtestingviruses

Identifiers

PMID35532013
PMCPMC9084890
OpenAlexW4229372036

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.