Evidence map›Paper›PMID 34523989›Full record

ArticleMicrobiology spectrum2021

Laboratory-Generated DNA Can Cause Anomalous Pathogen Diagnostic Test Results.

Lindsey R Robinson-McCarthy, Alexander J Mijalis, Gabriel T Filsinger, Helena de Puig, Nina M Donghia, Thomas E Schaus, Robert A Rasmussen, Raphael Ferreira, Jeantine E Lunshof, George Chao and 13 more

Open access · goldAbstract read
In one paragraph

Article in Microbiology spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-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

10 citing papers in PubMed, 17 citations in OpenAlex.

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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

23 authors at 5 institutions in 3 countries.

Lindsey R Robinson-McCarthy *Department of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Alexander J Mijalis *Department of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Gabriel T FilsingerDepartment of Systems Biology, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Helena de PuigWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Nina M DonghiaWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Thomas E SchausWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Robert A RasmussenWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Raphael FerreiraDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Jeantine E LunshofWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
George ChaoDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Dmitry Ter-OvanesyanWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Oliver DoddDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Erkin KuruDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Adama M SesayWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Joshua RainbowWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Andrew C PawlowskiDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Timothy M WannierDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Nicolaas M Angenent-MariWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Devora NajjarWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Peng YinWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.
Donald E IngberWyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA.ORCID 0000-0002-4319-6520
Jenny M TamDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.ORCID 0000-0002-3767-7205
George M ChurchDepartment of Genetics, Harvard Medical Schoolgrid.471403.5, Boston, Massachusetts, USA.
Harvard University · USMassachusetts Institute of Technology · USBoston Children's Hospital · USUniversity Medical Center Groningen · NLUniversity of Bath · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has brought about the unprecedented expansion of highly sensitive molecular diagnostics as a primary infection control strategy. At the same time, many laboratories have shifted focus to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) research and diagnostic development, leading to large-scale production of SARS-CoV-2 nucleic acids that can interfere with these tests. We have identified multiple instances, in independent laboratories, in which nucleic acids generated in research settings are suspected to have caused researchers to test positive for SARS-CoV-2 in surveillance testing. In some cases, the affected individuals did not work directly with these nucleic acids but were exposed

Indexed as

DNA ContaminationCOVID-19COVID-19 Nucleic Acid TestingDNA, ViralFalse Positive ReactionsHumansMolecular Diagnostic TechniquesRNA, ViralSARS-CoV-2DNA, ViralRNA, ViralCOVID-19diagnosticsnucleic acidsSARS-CoV-2

Identifiers

PMID34523989
PMCPMC8557887
OpenAlexW3200541566

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.