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DNA origami presenting the receptor binding domain of SARS-CoV-2 elicit robust protective immune response.


ABSTRACT: Effective and safe vaccines are invaluable tools in the arsenal to fight infectious diseases. The rapid spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 pandemic has highlighted the need to develop methods for rapid and efficient vaccine development. DNA origami nanoparticles (DNA-NPs) presenting multiple antigens in prescribed nanoscale patterns have recently emerged as a safe, efficient, and easily scalable alternative for rational design of vaccines. Here, we are leveraging the unique properties of these DNA-NPs and demonstrate that precisely patterning ten copies of a reconstituted trimer of the receptor binding domain (RBD) of SARS-CoV-2 along with CpG adjuvants on the DNA-NPs is able to elicit a robust protective immunity against SARS-CoV-2 in a mouse model. Our results demonstrate the potential of our DNA-NP-based approach for developing safe and effective nanovaccines against infectious diseases with prolonged antibody response and effective protection in the context of a viral challenge.

SUBMITTER: Oktay E 

PROVIDER: S-EPMC10034259 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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DNA origami presenting the receptor binding domain of SARS-CoV-2 elicit robust protective immune response.

Oktay Esra E   Alem Farhang F   Hernandez Keziah K   Girgis Michael M   Green Christopher C   Mathur Divita D   Medintz Igor L IL   Narayanan Aarthi A   Veneziano Remi R  

Communications biology 20230323 1


Effective and safe vaccines are invaluable tools in the arsenal to fight infectious diseases. The rapid spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease 2019 pandemic has highlighted the need to develop methods for rapid and efficient vaccine development. DNA origami nanoparticles (DNA-NPs) presenting multiple antigens in prescribed nanoscale patterns have recently emerged as a safe, efficient, and easily scalable alternative for r  ...[more]

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