Evidence map›Paper›PMID 40193039›Full record

ArticleMolecular biotechnology2026

Development of an ELISA Test with High Diagnostic Accuracy for SARS-COV-2 Using Recombinant Nucleocapsid Protein Expressed in E. coli.

Mahsa Darestanifarahani, Faezeh Mahmoudi, Ali Mohammadi, Ehsan Lotfi, Bahar Bahrami, Samira Shajari, Fatemeh Hamzehlooy, Fatemeh Karamali, Mahmood Barati, Davod Jafari

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Article in Molecular biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

10 authors.

Mahsa DarestanifarahaniCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Faezeh MahmoudiCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Ali MohammadiCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Ehsan LotfiCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Bahar BahramiCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Samira ShajariCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Fatemeh HamzehlooyCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
Fatemeh KaramaliDepartment of Medical Biotechnology, Faculty of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran.
Mahmood BaratiCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran. mahmood.barati@gmail.com.ORCID http://orcid.org/0000-0002-9663-9313
Davod JafariCellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran. Jafari.dt@gmail.com.ORCID http://orcid.org/0000-0002-2796-9597

Funding

Iran University of Medical Sciences 17893
6 · The paper itself

Abstract

This study aimed to produce a recombinant N protein to develop an enzyme-linked immunosorbent assay (ELISA). A recombinant pET28a vector was constructed, and E. coli BL 21 was transformed for recombinant protein expression. After SDS-PAGE analysis, we approved recombinant N protein expression and purification using western and dot-blotting tests. In ELISA setup tests, 2.5 µg/ml of N protein and 1:100 serum dilution was determined as optimum concentrations for anti-N IgG antibody. In validation tests, 47 out of 51 negative and 46 out of 51 positive samples were determined negative and positive, respectively, using our developed ELISA. According to the Receiver Operating Characteristic (ROC) curve analysis based on the Youden index, the sensitivity and specificity of the developed test were 92% and 90.38%, respectively. An ELISA test with the recombinant SARS-CoV-2 N protein was developed with high specificity and sensitivity for the clinical diagnosis of SARS-CoV-2 infection.

Indexed as

Coronavirus Nucleocapsid ProteinsCOVID-19COVID-19 Serological TestingPhosphoproteinsSARS-CoV-2Antibodies, ViralEnzyme-Linked Immunosorbent AssayEscherichia coliHumansImmunoglobulin GRecombinant ProteinsROC CurveSensitivity and SpecificityAntibodies, ViralCoronavirus Nucleocapsid ProteinsImmunoglobulin Gnucleocapsid phosphoprotein, SARS-CoV-2PhosphoproteinsRecombinant ProteinsCOVID-19ELISANucleocapsid proteinRecombinant proteinSARS-CoV-2

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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.