Evidence map›Paper›PMID 33790878›Full record

ArticleFrontiers in microbiology2021

Detection of Microbial Agents in Oropharyngeal and Nasopharyngeal Samples of SARS-CoV-2 Patients.

Tyler Seckar, Xiang Lin, Dipayan Bose, Zhi Wei, Joseph Rohrbaugh, Ronald G Collman, Erle S Robertson

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 98% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 2 institutions in 1 country.

Tyler SeckarDepartment of Otorhinolaryngology-Head and Neck Surgery, and Microbiology, The Tumor Virology Program, Abramson Comprehensive Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Xiang LinDepartment of Computer Science, New Jersey Institute of Technology, Newark, NJ, United States.
Dipayan BoseDepartment of Otorhinolaryngology-Head and Neck Surgery, and Microbiology, The Tumor Virology Program, Abramson Comprehensive Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Zhi WeiDepartment of Computer Science, New Jersey Institute of Technology, Newark, NJ, United States.
Joseph RohrbaughDepartment of Otorhinolaryngology-Head and Neck Surgery, and Microbiology, The Tumor Virology Program, Abramson Comprehensive Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Ronald G CollmanSchool of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Erle S RobertsonDepartment of Otorhinolaryngology-Head and Neck Surgery, and Microbiology, The Tumor Virology Program, Abramson Comprehensive Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
University of Pennsylvania · USNew Jersey Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus outbreak started in December 2019 and rapidly spread around the globe, leading to a global pandemic. Here we reported the association of microbial agents identified in oropharyngeal and nasopharyngeal samples from patients with SARS-CoV-2 infection, using a Pan-microarray based technology referred to as PathoChIP. To validate the efficiency of PathoChIP, reference viral genomes obtained from BEI resource and 25 SARS-CoV-2 positive clinical samples were tested. This technology successfully detected femtogram levels of SARS-CoV-2 viral RNA, which demonstrated greater sensitivity and specificity than conventional diagnostic techniques. Simultaneously, a broad range of other microorganisms, including other viruses, bacteria, fungi and parasites can be detected in those samples. We identified 7 viral, 12 bacterial and 6 fungal agents common across all clinical samples suggesting an associated microbial signature in individuals who are infected with SARS-CoV-2. This technology is robust and has a flexible detection methodology that can be employed to detect the presence of all human respiratory pathogens in different sample preparations with precision. It will be important for differentiating the causative agents of respiratory illnesses, including SARS-CoV-2.

Indexed as

COVID-19microbesPathoChIPprobesrespiratory agentsSARS-COV-2

Identifiers

PMID33790878
PMCPMC8006406
OpenAlexW3134906543

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.