Evidence map›Paper›PMID 37121656›Full record

ArticleAnalytica chimica acta2023

Aptamer-based nanointerferometer enables amplification-free ultrasensitive detection and differentiation of SARS-CoV-2 variants.

Changtian Chen, Xiaohui Song, Yuanling Yu, Xingwei Wang, Hua Xu, Weiwei Ji, Jingchen Ma, Chenyan Zhao, Silu Feng, Youchun Wang and 2 more

Open access · greenAbstract read
In one paragraph

Article in Analytica chimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

12 authors at 4 institutions in 1 country.

Changtian ChenState Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China; Center for Life Sciences, Beijing, 100871, China.
Xiaohui SongState Key Laboratory of Protein and Plant Gene Research, And Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China.
Yuanling YuChangping Laboratory, Yard 28, Science Park Road, Changping District, Beijing, China.
Xingwei WangState Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China.
Hua XuState Key Laboratory of Protein and Plant Gene Research, And Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China.
Weiwei JiCollege of Physics and Electronic Science, Hubei Normal University, Hubei, 435002, China.
Jingchen MaSchool of Materials and Energy, Guangdong University of Technology, Guangzhou, 510006, China.
Chenyan ZhaoDivision of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, 102629, China.
Silu FengSchool of Integrated Circuits, Guangdong University of Technology, Guangzhou, 510006, China. Electronic address: siluf@gdut.edu.cn.
Youchun WangDivision of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, 102629, China; Changping Laboratory, Yard 28, Science Park Road, Changping District, Beijing, China. Electronic address: wangyc@nifdc.org.cn.
Xiao-Dong SuState Key Laboratory of Protein and Plant Gene Research, And Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, 100871, China. Electronic address: xdsu@pku.edu.cn.
Wei WangState Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China; Center for Life Sciences, Beijing, 100871, China. Electronic address: oneway1985@pku.edu.cn.
Peking University · CNGuangdong University of Technology · CNNational Institutes for Food and Drug Control · CNHubei Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The state-of-the-art SARS-CoV-2 detection methods include qRT-PCR and antibody-based lateral flow assay (LFA) point-of-care tests. Despite the high sensitivity and selectivity, qRT-PCR is slow, expensive and needs well-trained operators. On the other extreme, LFA suffers from low sensitivity albeit its fast detection speed, low detection cost and ease of use. Therefore, the continuing COVID-19 pandemic calls for a SARS-CoV-2 detection method that is rapid, convenient and cost-effective without compromise in sensitivity. Here we provide a proof-of-principle demonstration of an optimized aptamer-based nanointerferometer that enables rapid and amplification-free detection of SARS-CoV-2 spike protein-coated pseudovirus directly from human saliva with the limit of detection (LOD) of about 400 copies per mL. This LOD is on par with that of qRT-PCR, making it 1000 to 100,000-fold more sensitive than commercial LFA tests. Using various combinations of negative selections during the screens for the aptamer targeting the receptor binding domain of the spike protein of SARS-CoV-2, we isolated two aptamers that can distinguish the Omicron and Delta variants. Integrating these two aptamers with LFA strips or the nanointerferometer sensors allows both detection and differentiation of the Omicron and Delta variants which has the potential to realize rapid triage of patients infected different SARS-CoV-2 variants.

Indexed as

COVID-19SARS-CoV-2HumansOligonucleotidesPandemicsSpike Glycoprotein, CoronavirusOligonucleotidesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Aptamer selectionNanointerferometerSARS-CoV-2 detection and differentiation

Identifiers

PMID37121656
PMCPMC10085716
OpenAlexW4363679261

What OpenQuestion holds

Textmetadata
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.