期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2015
卷号：112
期号：15
页码：4749-4754
DOI：10.1073/pnas.1502864112
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：SignificanceArboviruses (arthropod-borne viruses), a large group of RNA viruses, replicate in insects that transmit them to mammals, their second host. Insects and mammals have evolved different protein encoding strategies (codon pair bias); hence, arboviruses must delicately balance their encodings between two phyla. Using dengue virus (DENV), the most important human arbovirus pathogen, as a model, we have, by computer design and chemical synthesis, undone this balance in codon pair bias in favor of insects. Recoded DENVs grow well in insect cells but are highly attenuated in mammalian cells and in suckling mice. This unique approach offers a previously unidentified possibility to rapidly develop new vaccine candidates against DENV and perhaps against many different human arboviruses. The protein synthesis machineries of two distinct phyla of the Animal kingdom, insects of Arthropoda and mammals of Chordata, have different preferences for how to best encode proteins. Nevertheless, arboviruses (arthropod-borne viruses) are capable of infecting both mammals and insects just like arboviruses that use insect vectors to infect plants. These organisms have evolved carefully balanced genomes that can efficiently use the translational machineries of different phyla, even if the phyla belong to different kingdoms. Using dengue virus as an example, we have undone the genome encoding balance and specifically shifted the encoding preference away from mammals. These mammalian-attenuated viruses grow to high titers in insect cells but low titers in mammalian cells, have dramatically increased LD50s in newborn mice, and induce high levels of protective antibodies. Recoded arboviruses with a bias toward phylum-specific expression could form the basis of a new generation of live attenuated vaccine candidates.
