Evidence map›Paper›PMID 39194145›Full record

ArticleEmerging microbes & infections2024

Streamlined detection of Nipah virus antibodies using a split NanoLuc biosensor.

Éric Bergeron, Cheng-Feng Chiang, Michael K Lo, Elif Karaaslan, Syed Moinuddin Satter, Mohammed Ziaur Rahman, Mohammad Enayet Hossain, Wasik Rahman Aquib, Dewan Imtiaz Rahman, Subyeta Binte Sarwar and 3 more

Abstract read
In one paragraph

Article in Emerging microbes & infections, 2024. 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
–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

9 citing papers in PubMed.

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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

13 authors.

Éric BergeronViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0003-3398-8628
Cheng-Feng ChiangViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0002-3617-9124
Michael K LoViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0002-0409-7896
Elif KaraaslanViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0002-5097-8854
Syed Moinuddin Sattericddr,b, Dhaka, Bangladesh.ORCID 0000-0002-2959-4522
Mohammed Ziaur Rahmanicddr,b, Dhaka, Bangladesh.ORCID 0000-0002-4103-4835
Mohammad Enayet Hossainicddr,b, Dhaka, Bangladesh.ORCID 0000-0001-5511-1857
Wasik Rahman Aquibicddr,b, Dhaka, Bangladesh.ORCID 0009-0000-1412-298X
Dewan Imtiaz Rahmanicddr,b, Dhaka, Bangladesh.ORCID 0009-0006-2337-6766
Subyeta Binte Sarwaricddr,b, Dhaka, Bangladesh.
Joel M MontgomeryViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0003-0523-4431
John D KlenaViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0001-9933-6193
Christina F SpiropoulouViral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, USA.ORCID 0000-0001-8406-3161

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nipah virus (NiV) is an emerging zoonotic RNA virus that can cause fatal respiratory and neurological diseases in animals and humans. Accurate NiV diagnostics and surveillance tools are crucial for the identification of acute and resolved infections and to improve our understanding of NiV transmission and circulation. Here, we have developed and validated a split NanoLuc luciferase NiV glycoprotein (G) biosensor for detecting antibodies in clinical and animal samples. This assay is performed by simply mixing reagents and measuring luminescence, which depends on the complementation of the split NanoLuc luciferase G biosensor following its binding to antibodies. This anti-NiV-G "mix-and-read" assay was validated using the WHO's first international standard for anti-NiV antibodies and more than 700 serum samples from the NiV-endemic country of Bangladesh. Anti-NiV antibodies from survivors persisted for at least 8 years according to both ⍺NiV-G mix-and-read and NiV neutralization assays. The ⍺NiV-G mix-and-read assay sensitivity (98.6%) and specificity (100%) were comparable to anti-NiV IgG ELISA performance but failed to detect anti-NiV antibodies in samples collected less than a week following the appearance of symptoms. Overall, the anti-NiV-G biosensor represents a simple, fast, and reliable tool that could support the expansion of NiV surveillance and retrospective outbreak investigations.

Indexed as

Antibodies, ViralBiosensing TechniquesHenipavirus InfectionsNipah VirusAdolescentAdultAnimalsBangladeshEnzyme-Linked Immunosorbent AssayFemaleHumansLuciferasesMaleMiddle AgedSensitivity and SpecificityYoung AdultAntibodies, ViralLuciferasesantibodiesdisease surveillanceNipah virusparamyxoviridaeserology

Identifiers

PMID39194145
PMCPMC11391874

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Registered trials

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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.