Evidence map›Paper›PMID 35638906›Full record

ArticleMicrobiology spectrum2022

Receptor-Binding-Motif-Targeted Sanger Sequencing: a Quick and Cost-Effective Strategy for Molecular Surveillance of SARS-CoV-2 Variants.

Sankar Prasad Chaki, Melissa M Kahl-McDonagh, Benjamin W Neuman, Kurt A Zuelke

Open access · goldAbstract read
In one paragraph

Article in Microbiology spectrum, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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

4 authors at 1 institution in 1 country.

Sankar Prasad ChakiTexas A&M Global Health Research Complex, Division of Research, Texas A&M University, College Station, Texas, USA.ORCID 0000-0002-8130-6997
Melissa M Kahl-McDonaghTexas A&M Global Health Research Complex, Division of Research, Texas A&M University, College Station, Texas, USA.
Benjamin W NeumanTexas A&M Global Health Research Complex, Division of Research, Texas A&M University, College Station, Texas, USA.
Kurt A ZuelkeTexas A&M Global Health Research Complex, Division of Research, Texas A&M University, College Station, Texas, USA.
Texas A&M University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-genome sequencing (WGS) is the gold standard for characterizing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome and identification of new variants. However, the cost involved and time needed for WGS prevent routine, rapid clinical use. This study aimed to develop a quick and cost-effective surveillance strategy for SARS-CoV-2 variants in saliva and nasal swab samples by spike protein receptor-binding-motif (RBM)-targeted Sanger sequencing. Saliva and nasal swabs prescreened for the presence of the nucleocapsid (N) gene of SARS-CoV-2 were subjected to RBM-specific single-amplicon generation and Sanger sequencing. Sequences were aligned by CLC Sequence Viewer 8, and variants were identified based upon specific mutation signature. Based on this strategy, the present study identified Alpha, Beta/Gamma, Delta, and Omicron variants in a quick and cost-effective manner.

Indexed as

COVID-19SARS-CoV-2Cost-Benefit AnalysisGenome, ViralHumansMutationPandemicsAlpha variantDelta variantlineagesmutationsOmicron variantreceptor-binding motif (RBM)Sanger sequencingSARS-CoV-2variant surveillance

Identifiers

PMID35638906
PMCPMC9241651
OpenAlexW4281622676

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.