Evidence map›Paper›PMID 32501446›Full record

ArticleBiosafety and health2019

A novel luciferase immunosorbent assay performs better than a commercial enzyme-linked immunosorbent assay to detect MERS-CoV specific IgG in humans and animals.

Wenling Wang, Tianyu Wang, Yao Deng, Peihua Niu, Ruhan A, Jincun Zhao, Malik Peiris, Shixing Tang, Wenjie Tan

Open access · goldAbstract read
In one paragraph

Article in Biosafety and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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

9 authors at 6 institutions in 2 countries.

Wenling WangMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
Tianyu WangMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
Yao DengMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
Peihua NiuMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
Ruhan AMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
Jincun ZhaoState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Disease, The first Affiliated Hospital of Guangzhou Medical University, Guangzhou 510182, China.
Malik PeirisSchool of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region.
Shixing TangGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China.
Wenjie TanMHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China.
National Institute for Viral Disease Control and Prevention · CNChinese Center For Disease Control and Prevention · CNChinese Academy of Sciences · CNFirst Affiliated Hospital of Guangzhou Medical University · CNSouthern Medical University · CNUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Middle East respiratory syndrome (MERS) is a lethal zoonosis caused by MERS coronavirus (MERS-CoV) and poses a significant threat to public health worldwide. Therefore, a rapid, sensitive, and specific serologic test for detecting anti-MERS-CoV antibodies in both humans and animals is urgently needed for the successful management of this illness. Here, we evaluated various novel luciferase immunosorbent assays (LISA) based on nucleocapsid protein (NP) as well as fragments derived from spike protein (S) including subunit 1 (S1), N terminal domain (NTD), receptor-binding domain (RBD) and subunit 2 (S2) of S for the detection of MERS-CoV-specific IgG. Fusion proteins, including nanoluciferase (NLuc) and various fragments derived from the NP or S protein of MERS-CoV, were expressed in human embryonic kidney 293 T cells. LISAs that detected anti-MERS-CoV IgG were further developed using cell lysates expressing various fusion proteins. Panels of human or animal samples infected with MERS-CoV were used to analyze the sensitivity and specificity of various LISAs in reference to a MERS-CoV RT-PCR, commercial S1-based ELISA, and pseudovirus particle neutralization test (ppNT). Our results showed that the S1-, RBD-, and NP-LISAs were more sensitive than the NTD- and S2-LISAs for the detection of anti-MERS-CoV IgG. Furthermore, the S1-, RBD-, and NP-LISAs were more sensitive (by at least 16-fold) than the commercially available S1-ELISA. Moreover, the S1-, RBD-, and NP-LISA specifically recognized anti-MERS-CoV IgG and did not cross-react with samples derived from other human CoV (OC43, 229E, HKU1, NL63)-infected patients. More importantly, these LISAs proved their applicability and reliability for detecting anti-MERS-CoV IgG in samples from camels, monkeys, and mice, among which the RBD-LISA exhibited excellent performance. The results of this study suggest that the novel MERS-CoV RBD- and S1- LISAs are highly effective platforms for the rapid and sensitive detection of anti-MERS-CoV IgG in human and animal samples. These assays have the potential to be used as serologic tests for the management and control of MERS-CoV infection.

Indexed as

Luciferase immunosorbent assay (LISA)MERS-CoVSamples of humans and animalsSerological IgG detection

Identifiers

PMID32501446
PMCPMC7148641
OpenAlexW2994968171

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.