A Mammalian Surface Display Platform to Optimize the Antigenicity of Viral Proteins for Vaccine Design

preprint OA: closed
Full text JSON View at publisher
Full text 1,545 characters · extracted from oa-doi-fallback · click to expand
Abstract Vaccine development often involves modifying native viral proteins to enhance their stability and antigenicity, as seen in approved Covid-19 vaccines and multiple HIV vaccine candidates currently under investigation. High throughput screening on the surface of mammalian cells enables the rapid evaluation of oligomeric, glycosylated viral proteins and the identification of mutations that improve their properties for vaccine design. Here, we developed an experimental platform that uses the PiggyBac transposon system to display libraries of viral protein variants on the surface of mammalian cells for efficient screening. This approach addresses common challenges in existing mammalian display systems, including low transfection efficiency and the development of stable cell lines for iterative selection rounds. The new platform was validated by expressing and characterizing antigenically diverse viral proteins from influenza, SARS-CoV-2, and HIV. In a further application, library screening of influenza haemagglutinin libraries identified mutations that increased binding of broadly cross-reactive antibodies to a conserved, but partially occluded, epitope of interest for the development of a universal influenza vaccine. These results demonstrate the potential of this mammalian display platform to rapidly engineer immunogens with desired antigenic properties for vaccine design. Competing Interest Statement The authors have declared no competing interest. Footnotes The revision was done to change the authors' positions.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00