Machine learning-assisted design of a dendritic cell nanovaccine inducing twin immunity against monkeypox.

Journal: Journal of controlled release : official journal of the Controlled Release Society
Published Date:

Abstract

The global emergence of monkeypox virus (MPXV) has created an urgent need for effective vaccines that induce robust immune responses. Here, we report a biomimetic nano-vaccine platform based on engineered dendritic cell membrane vesicles displaying M1R (M1R-CMVs), designed via genetic engineering with machine learning-assisted preliminary screening of physicochemical parameters including particle size (~190 nm) and zeta potential (-18 mV). Subcutaneous delivery of M1R-CMVs with CpG adjuvant induced high titers of M1R-specific IgG and potent neutralizing antibodies. The vaccine promoted broad T cell activation, characterized by enhanced CD4+ and CD8+ T cell responses in spleen and lymph nodes, and established durable T cell memory. In vitro studies demonstrated that M1R-CMVs enhance dendritic cell maturation and T cell proliferation. Prime-boost immunization further amplified both humoral and cellular immunity, with significant increases in neutralizing antibody titers and effector T cell populations. Furthermore, the vaccine exhibited a favorable safety profile in vivo with no significant toxicity observed. Our findings demonstrate a biomimetic vaccine design strategy integrating engineered vesicles with machine learning-assisted physicochemical analysis, providing a promising approach to combat monkeypox.

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