ArticleJournal of immunology (Baltimore, Md. : 1950)2025
Non-neutralizing antibodies against SARS-CoV-2 nucleocapsid protein mediate variant transcendent antibody-dependent cellular cytotoxicity.
Article in Journal of immunology (Baltimore, Md. : 1950), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Impact of Maternal COVID-19 Infection Versus Vaccination on Mucosal Immunity in Breastmilk.Journal of clinical medicine · 2026Article
- SARS-CoV-2 Variants and Immune Evasion: Mapping the Future of Vaccine Design.Reviews in medical virology · 2026Review
- Measuring Humoral Immune Responses to SARS-CoV-2: A Comprehensive Review of Serological Assays.Vaccines · 2026Review
- The Unexpected Visibility of the SARS-CoV-2 Nucleocapsid Protein Reveals a Hidden Route of Surface Trafficking.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Vaccination strategies and correlates of protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have predominantly focused on the spike (S) protein and neutralizing antibodies. However, the rapid emergence of SARS-CoV-2 variants has reduced the effectiveness of spike-based vaccines and monoclonal antibodies. It remains unclear how non-neutralizing antibodies that target the nucleocapsid (N) protein contribute to protection against SARS-CoV-2 variants, especially their ability to trigger antibody effector functions. These antibodies may function by binding to infected cells and initiating antibody-dependent cellular cytotoxicity (ADCC), eliminating infected cells. In this study, we demonstrate that antibodies from individuals who recovered from coronavirus disease 2019 (COVID-19) infection and/or were vaccinated with the S protein vaccine recognize viral proteins on the surface of infected cells and mediate ADCC-mediated NK cell killing of infected cells. Notably, non-neutralizing antibodies induced in COVID-19 infection recognized non-spike proteins on the surface of SARS-CoV-2 variant-infected cells, and these non-neutralizing antibodies cleared SARS-CoV-2 infected cells following depletion of spike antibodies. We identified N and minimal membrane (M) proteins as the targets of non-neutralizing antibodies on the surface of these variant-infected cells. We show that enriched N-specific antibodies from individuals who recovered from COVID-19 infection more consistently killed SARS-CoV-2 variant-infected cells than antibodies to the spike protein. The observed cross-reactivity and robust ADCC activity mediated by N-specific antibodies across various SARS-CoV-2 variant-infected cells highlight the N protein as an important vaccine target in addition to the S protein. Targeting N may provide more comprehensive and durable immunity against SARS-CoV-2 and its evolving variants.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.