Multiscale analysis for patterns of Zika virus genotype emergence, spread, and consequence.

The question of how Zika virus (ZIKV) changed from a seemingly mild virus to a human pathogen capable of microcephaly and sexual transmission remains unanswered. The unexpected emergence of ZIKV's pathogenicity and capacity for sexual transmission may be due to genetic changes, and future changes in phenotype may continue to occur as the virus expands its geographic range. Alternatively, the sheer size of the 2015-16 epidemic may have brought attention to a pre-existing virulent ZIKV phenotype in a highly susceptible population. Thus, it is important to identify patterns of genetic change that may yield a better understanding of ZIKV emergence and evolution. However, because ZIKV has an RNA genome and a polymerase incapable of proofreading, it undergoes rapid mutation which makes it difficult to identify combinations of mutations associated with viral emergence. As next generation sequencing technology has allowed whole genome consensus and variant sequence data to be generated for numerous virus samples, the task of analyzing these genomes for patterns of mutation has become more complex. However, understanding which combinations of mutations spread widely and become established in new geographic regions versus those that disappear relatively quickly is essential for defining the trajectory of an ongoing epidemic. In this study, multiscale analysis of the wealth of genomic data generated over the course of the epidemic combined with in vivo laboratory data allowed trends in mutations and outbreak trajectory to be assessed. Mutations were detected throughout the genome via deep sequencing, and many variants appeared in multiple samples and in some cases become consensus. Similarly, amino acids that were previously consensus in pre-outbreak samples were detected as low frequency variants in epidemic strains. Protein structural models indicate that most of the mutations associated with the epidemic transmission occur on the exposed surface of viral proteins. At the macroscale level, consensus data was organized into large and interactive databases to allow the spread of individual mutations and combinations of mutations to be visualized and assessed for temporal and geographical patterns. Thus, the use of multiscale modeling for identifying mutations or combinations of mutations that impact epidemic transmission and phenotypic impact can aid the formation of hypotheses which can then be tested using reverse genetics.

Colocalized delivery of adjuvant and antigen using nanolipoprotein particles enhances the immune response to recombinant antigens.

Subunit antigen-based vaccines can provide a number of important benefits over traditional vaccine candidates, such as overall safety. However, because of the inherently low immunogenicity of these antigens, methods for colocalized delivery of antigen and immunostimulatory molecules (i.e., adjuvants) are needed. Here we report a robust nanolipoprotein particle (NLP)-based vaccine delivery platform that facilitates the codelivery of both subunit antigens and adjuvants. Ni-chelating NLPs (NiNLPs) were assembled to incorporate the amphipathic adjuvants monophosphoryl lipid A and cholesterol-modified CpG oligodeoxynucleotides, which can bind His-tagged protein antigens. Colocalization of antigen and adjuvant delivery using the NiNLP platform resulted in elevated antibody production against His-tagged influenza hemagglutinin 5 and Yersinia pestis LcrV antigens. Antibody titers in mice immunized with the adjuvanted NLPs were 5-10 times higher than those observed with coadministration formulations and nonadjuvanted NiNLPs. Colocalized delivery of adjuvant and antigen provides significantly greater immune stimulation in mice than coadministered formulations.

Magnetic bead based immunoassay for autonomous detection of toxins.

We are developing an automated system for the simultaneous, rapid detection of a group of select agents and toxins in the environment. To detect toxins, we modified and automated an antibody-based approach previously developed for manual medical diagnostics that uses fluorescent eTag reporter molecules and is suitable for highly multiplexed assays. Detection is based on two antibodies binding simultaneously to a single antigen, one of which is labeled with biotin while the other is conjugated to a fluorescent eTag through a cleavable linkage. Aqueous samples are incubated with the mixture of antibodies along with streptavidin-coated magnetic beads and a photoactive porphyrin complex. In the presence of antigen, a molecular complex is formed where the cleavable linkage is held in proximity to the photoactive group. Upon excitation at 680 nm, free radicals are generated, which diffuse and cleave the linkage, releasing the eTags. Released eTags are analyzed using capillary gel electrophoresis with laser-induced fluorescence detection. Limits of detection for ovalbumin and botulinum toxoid individually were 4 (or 80 pg) and 16 ng/mL (or 320 pg), respectively, using the manual assay. In addition, we demonstrated the use of pairs of antibodies from different sources in a single assay to decrease the rate of false positives. Automation of the assay was demonstrated in a flow-through format with higher LODs of 32 ng/mL (or 640 ng) each of a mixture of ovalbumin and botulinum toxoid. This versatile assay can be easily modified with the appropriate antibodies to detect a wide range of toxins and other proteins.