Evidence map›Paper›PMID 34787499›Full record

ArticleMicrobiology spectrum2021

A Novel Strategy for the Detection of SARS-CoV-2 Variants Based on Multiplex PCR-Mass Spectrometry Minisequencing Technology.

Fei Zhao, Jinxing Lu, Bing Lu, Tian Qin, Xuemei Wang, Xuexin Hou, Fanliang Meng, Xiaona Xu, Tianyi Li, Haijian Zhou and 5 more

Abstract 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 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. 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

15 authors.

Fei ZhaoNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Jinxing LuNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Bing LuInstitute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Tian QinNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Xuemei WangIntelligene Biosystems (Qingdao) Co., Ltd., Qingdao, China.
Xuexin HouNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Fanliang MengNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Xiaona XuNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Tianyi LiNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.ORCID 0000-0001-5853-1216
Haijian ZhouNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Jianzhong ZhangNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Biao KanNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.ORCID 0000-0002-6141-4552
Ying HuangInstitute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Zehui ZhangNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.
Di XiaoNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, State Key Laboratory of Infectious Disease Prevention and Control, Beijing, China.ORCID 0000-0002-5964-5925

Funding

The major infectious diseases AIDS and viral hepatitis prevention and control technology major projects 2018ZX10712001-006012
6 · The paper itself

Abstract

The objective of this study was to construct a novel strategy for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants using multiplex PCR-mass spectrometry minisequencing technique (mPCR-MS minisequencing). Using the nucleic acid sequence of a SARS-CoV-2 nonvariant and a synthetic SARS-CoV-2 variant-carrying plasmid, a matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) method based on the single-base mass probe extension of multiplex PCR amplification products was established to detect 9 mutation types in 7 mutated sites (HV6970del, N501Y, K417N, P681H, D614G, E484K, L452R, E484Q, and P681R) in the receptor-binding domain of the spike protein of SARS-CoV-2 variants. Twenty-one respiratory tract pathogens (9 bacteria and 12 respiratory viruses) and nucleic acid samples from non-COVID-19 patients were selected for specific validation. Twenty samples from COVID-19 patients were used to verify the accuracy of this method. The 9 mutation types could be detected simultaneously by triple PCR amplification coupled with MALDI-TOF MS. SARS-CoV-2 and six variants, B.1.1.7 (Alpha), B.1.351 (Beta), B.1.429 (Epsilon), B.1.526 (Iota), P.1 (Gamma) and B.1.617.2 (Delta), could be identified. The detection limit for all 9 sites was 1.5 × 10

Indexed as

Base SequenceCOVID-19COVID-19 TestingHumansMass SpectrometryMultiplex Polymerase Chain ReactionMutationPolymorphism, Single NucleotideProtein BindingReal-Time Polymerase Chain ReactionSARS-CoV-2Spike Glycoprotein, CoronavirusWhole Genome SequencingSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2mPCR-MS minisequencingSARS-CoV-2 variantsscreening and identificationSNPs

Identifiers

PMID34787499
PMCPMC8597632

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.