A Binary RNA and DNA Self-Amplifying Platform for Next Generation Vaccines and Therapeutics (preprint)

Conventional mRNA-based vaccines were instrumental in lowering the burden of the pandemic on healthcare systems and in reducing mortality. However, such first-generation vaccines have significant weaknesses. Here, we describe a high-performance binary recombinant vectoral platform offering the flexibility to be used as a self-amplifying mRNA or a self-amplifying DNA. Both formats drive long-lasting expression and actuate robust antibody responses against SAR-CoV-2 spike, and neither format require encapsulation with lipid nanoparticles (LNP) in the generation immune responses. The platform combines the power of conventional mRNA with the low-dosage of self-amplifying vectors together with the simplicity, rapid creation, ease of storage, and convenience of distribution of plasmid DNA vectors. This platform promises to pave the way for more effective, less expensive, and truly democratized vaccines and therapeutics.

Distinguishing imported cases from locally acquired cases within a geographically limited genomic sample of an infectious disease (preprint)

ABSTRACT The ability to distinguish imported cases from locally acquired cases has important consequences for the selection of public health control strategies. Genomic data can be useful for this, for example using a phylogeographic analysis in which genomic data from multiple locations is compared to determine likely migration events between locations. However, these methods typically require good samples of genomes from all locations, which is rarely available. Here we propose an alternative approach that only uses genomic data from a location of interest. By comparing each new case with previous cases from the same location we are able to detect imported cases, as they have a different genealogical distribution than that of locally acquired cases. We show that, when variations in the size of the local population are accounted for, our method has good sensitivity and excellent specificity for the detection of imports. We applied our method to data simulated under the structured coalescent model and demonstrate relatively good performance even when the local population has the same size as the external population. Finally, we applied our method to several recent genomic datasets from both bacterial and viral pathogens, and show that it can, in a matter of seconds or minutes, deliver important insights on the number of imports to a geographically limited sample of a pathogen population.

Transcriptomic Profiling of Dromedary Camels Immunised with a MERS Vaccine Candidate (preprint)

Middle East Respiratory Syndrome coronavirus (MERS-CoV) infects dromedary camels and zoonotically infects humans, causing a respiratory disease with severe pneumonia and death. With no approved antiviral or vaccine interventions for MERS, vaccines are being developed for camels to prevent virus transmission into humans. We have previously developed a chimpanzee adenoviral vector-based vaccine for MERS-CoV (ChAdOx1 MERS) and reported its strong humoral immunogenicity in dromedary camels. Here, we looked back at total RNA isolated from three immunised dromedaries pre and post-vaccination during the first day; and performed RNA sequencing and bioinformatic analysis in order to shed light on the molecular immune responses following a ChAdOx1 MERS vaccination. Our finding shows that a number of transcripts were differentially regulated as an effect of the vaccination, including genes that are involved in innate and adaptive immunity, such as type I and II interferon responses. The camel Bcl-3 and Bcl-6 transcripts were significantly upregulated, indicating a strong activation of Tfh cells, B cell, and NF-kB pathways. In conclusion, this study gives an overall view of the first changes in the immune transcriptome of dromedaries after vaccination; it supports the potency of ChAdOx1 MERS as a potential camel vaccine to block transmission and prevent new human cases and outbreaks.