Evidence map›Paper›PMID 35262087›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Identifying SARS-CoV-2 Variants of Concern through saliva-based RT-qPCR by targeting recurrent mutation sites.

Rachel E Ham, Austin R Smothers, Rui Che, Keegan J Sell, Congyue Annie Peng, Delphine Dean

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Rachel E HamCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Austin R SmothersCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Rui CheCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Keegan J SellCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Congyue Annie PengCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Delphine DeanCenter for Innovative Medical Devices and Sensors (REDDI Lab), Clemson University, Clemson, SC, USA.
Sensors (United States) · US

Funding

Tissue Structural and Neural Remodeling in Human Sacroiliac JointP20GM121342 · NIGMS · CLEMSON UNIVERSITY · PI Jeryl Jones · 2018 to 2026
$24.7M
NIGMS NIH HHS P20 GM121342
6 · The paper itself

Abstract

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to compliment whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60% and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20%, 96.40%, 99.60%, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from December 7-22, 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. Importance: SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our real-time RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between VOCs and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

Identifiers

PMID35262087
PMCPMC8902870
OpenAlexW4221103071

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.