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Engineering RNA viruses with unnatural amino acid to evoke adjustable immune response in mice
Preprint
in English
| bioRxiv
| ID: ppbiorxiv-471206
ABSTRACT
Ribonucleic acid (RNA) viruses pose heavy burdens on public-health systems. Synthetic biology holds great potential for artificially controlling their replication, a strategy that could be used to attenuate infectious viruses but is still in the exploratory stage. Herein, we used the genetic-code expansion technique to convert Enterovirus 71 (EV71), a model of RNA virus, into a controllable EV71 strain carrying the unnatural amino acid (UAA) N{varepsilon}-2-azidoethyloxycarbonyl-L-lysine (NAEK), which we termed an EV71-NAEK virus. EV71-NAEK could recapitulate an authentic NAEK time- and dose-dependent infection in vitro and in vivo, which could serve as a novel method to manipulate virulent viruses in conventional laboratories. We further validated the prophylactic effect of EV71-NAEK in two mouse models. In susceptible parent mice, vaccination with EV71-NAEK elicited a strong immune response and potentially protected their neonatal offspring from lethal challenge similar to that of commercial vaccines. Meanwhile, in transgenic mice harboring a PylRS-tRNAPyl pair, substantial elements of genetic-code expansion technology, EV71-NAEK evoked an adjustable neutralizing-antibody response in a strictly external NAEK dose-dependent manner. These findings suggested that EV71-NAEK could be the basis of a feasible immunization program for populations with different levels of immunity. Moreover, we expanded the strategy to generate controllable coxsackieviruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for conceptual verification. In combination, these results could underlie a competent strategy for attenuating viruses and priming the immune system via artificial control, which might be a promising direction for the development of amenable vaccine candidates and be broadly applied to other RNA viruses.
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Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Type of study:
Prognostic study
Language:
English
Year:
2021
Document type:
Preprint