mBaoJin-labeled pangolin coronavirus for evaluating population cross-neutralizing antibodies and the entry-inhibitory activity of cepharanthine
Ma, Y.; Lu, S.; Luo, S.; Hu, Y.; Zhang, X.; Deng, L.; Li, C.; Chen, W.; Zheng, W.; Song, L.
Show abstract
Replication-competent coronaviruses carrying fluorescent protein-tagged structural proteins remain scarce. Using the highly attenuated pangolin coronavirus GX_P2V(short_3UTR) as a backbone, we generated GX_P2V-mBJ-N, a recombinant coronavirus in which the bright green fluorescent protein mBaoJin is fused to the nucleocapsid (N) protein. The reporter virus is attenuated and genetically unstable in normal Vero cells but can be amplified to high titers in cells expressing wild-type N, and its fluorescence directly reports N protein expression. Using this authentic-virus platform, we show that high-titer GX_P2V cross-neutralizing antibodies persist in most healthy individuals and that cepharanthine potently blocks viral entry. GX_P2V-mBJ-N thus provides a simple and reliable tool for coronavirus tracing, immune surveillance, and antiviral drug evaluation.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Emergence of transmissible SARS-CoV-2 variants with decreased sensitivity to antivirals in immunocompromised patients with persistent infections 95%
- A live-attenuated SARS-CoV-2 vaccine candidate with accessory protein deletions 95%
- A non-spike nucleocapsid R204P mutation in SARS-CoV-2 Omicron XEC enhances inflammation and pathogenicity 94%
Similar papers in this journal
- Quantifying absolute neutralization titers against SARS-CoV-2 by a standardized virus neutralization assay allows for cross-cohort comparisons of COVID-19 sera 94%
- DAZAP2 functions as a pan-coronavirus restriction factor by inhibiting viral entry and genomic replication 94%
- Molecular insights into nucleocapsid assembly and transport in Marburg and Ebola viruses 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.