A Liposome-Based Nanoparticle Vaccine Induces Effective Immunity Against EBV Infection
Year: 2025
Type: article
Abstract: Background: Epstein-Barr virus (EBV) infects approximately 95% of the global population, causing numerous malignancy-related cases annually and some autoimmune diseases. EBV-encoded gp350, gH, gL, gp42 and gB glycoproteins are identified as antigen candidates for their key role in viral entry, and nanoparticle vaccines displaying them were developed for the advantage of inducing cross-reactive B cell responses. Methods: To develop liposomes displaying nanoparticle vaccine, we synthesized liposomes to present the well-identified EBV-encoded gp350D123 glycoprotein on their surface to imitate the viral structure, through the conjugation between N-hydroxysuccinimide (NHS) groups on the liposomes and primary amine of antigens to form stable amide bond. Then we assessed the immunogenicity of the biomimetic Lipo-gp350D123 nanoparticle vaccine in Balb/c mice immunized experiments. Results: The results showed that the sera samples from Lipo-gp350D123 nanoparticle vaccine immunized mice collected at weeks 8, 10 and 12 had higher titers of gp350D123 protein-specific antibodies, compared to monomer gp350D123 protein control, and higher titers of neutralizing antibodies to block EBV-GFP infection in AKATA cells. Meanwhile, the Lipo-gp350D123 nanoparticle vaccine also induced higher percentage of CD8+ IFN-γ+ T cells in the spleen, but without significance in CD4+ IFN-γ+ T cells, and these isolated splenocytes showed a higher level of secreted IFN-γ. Moreover, no significant histopathological changes were observed in all vaccinated mice. Conclusions: Altogether these data demonstrated that the liposome displaying promoted the immunogenicity of antigens, and the Lipo-gp350D123 nanoparticle vaccine candidate had potential application in blocking EBV infection. The liposome nanoparticle was a useful vector for antigen displaying to elicit effective immunity.
Source: Vaccines
Authors: Ping Li, Zihang Yu, Ziyi Jiang, Yike Jiang, Jingjing Shi, Sanyang Han, Lan Ma
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W4408923315
