A systems approach to designing next generation vaccines: combining α-galactose modified antigens with nanoparticle platforms.

Innovative vaccine platforms are needed to develop effective countermeasures against emerging and re-emerging diseases. These platforms should direct antigen internalization by antigen presenting cells and promote immunogenic responses. This work describes an innovative systems approach combining two novel platforms, αGalactose (αGal)-modification of antigens and amphiphilic polyanhydride nanoparticles as vaccine delivery vehicles, to rationally design vaccine formulations. Regimens comprising soluble αGal-modified antigen and nanoparticle-encapsulated unmodified antigen induced a high titer, high avidity antibody response with broader epitope recognition of antigenic peptides than other regimen. Proliferation of antigen-specific CD4(+) T cells was also enhanced compared to a traditional adjuvant. Combining the technology platforms and augmenting immune response studies with peptide arrays and informatics analysis provides a new paradigm for rational, systems-based design of next generation vaccine platforms against emerging and re-emerging pathogens.

Information-theoretic approach for the discovery of design rules for crystal chemistry.

In this work, it is shown that for the first time that, using information-entropy-based methods, one can quantitatively explore the relative impact of a wide multidimensional array of electronic and chemical bonding parameters on the structural stability of intermetallic compounds. Using an inorganic AB2 compound database as a template data platform, the evolution of design rules for crystal chemistry based on an information-theoretic partitioning classifier for a high-dimensional manifold of crystal chemistry descriptors is monitored. An application of this data-mining approach to establish chemical and structural design rules for crystal chemistry is demonstrated by showing that, when coupled with first-principles calculations, statistical inference methods can serve as a tool for significantly accelerating the prediction of unknown crystal structures.

Identification of biologically significant genes from combinatorial microarray data.

High-throughput microarray technology has enabled the simultaneous measurement of the abundance of tens of thousands of gene-expression levels, opening up a new variety of opportunities in both basic and applied biological research. In the wealth of genomic data produced so far, the analysis of massive volume of data sets has become a challenging part of this innovative approach. In this study, a series of microarray experimental data from Yersinia pestis (Y. pestis), the etiologic agent of plague in humans, were analyzed to investigate the effect of the treatments with quorum-sensing signal molecules (autoinducer-2 and acyl-homoserine lactones) and mutation (ΔypeIR, ΔyspIR, and ΔluxS) on the variation of gene-expression levels. The gene-expression data have been systematically analyzed to find potentially important genes for vaccine development by means of a coordinated use of statistical learning algorithms, that is, principal component analysis (PCA), gene shaving (GS), and self-organizing map (SOM). The results achieved from the respective methods, the lists of genes identified as differentially expressed, were combined to minimize the risk that might arise when using a single method. The commonly detected genes from multiple data mining methods, which reflect the linear/nonlinear dimensionality and similarity measure in gene-expression space, were taken into account as the most significant group. In conclusion, tens of potentially biologically significant genes were identified out of over 4000 genes of Y. pestis. The "active" genes discovered in this study will provide information on bacterial genetic targets important for the development of novel vaccines.

Activation of innate immune responses in a pathogen-mimicking manner by amphiphilic polyanhydride nanoparticle adjuvants.

Techniques in materials design, immunophenotyping, and informatics can be valuable tools for using a molecular based approach to design vaccine adjuvants capable of inducing protective immunity that mimics a natural infection but without the toxic side effects. This work describes the molecular design of amphiphilic polyanhydride nanoparticles that activate antigen presenting cells in a pathogen-mimicking manner. Biodegradable polyanhydrides are well suited as vaccine delivery vehicles due to their adjuvant-like ability to: 1) enhance the immune response, 2) preserve protein structure, and 3) control protein release. The results of these studies indicate that amphiphilic nanoparticles possess pathogen-mimicking properties as evidenced by their ability to activate dendritic cells similarly to LPS. Specific molecular descriptors responsible for this behavior were identified using informatics analyses, including the number of backbone oxygen moieties, percent of hydroxyl end groups, polymer hydrophobicity, and number of alkyl ethers. Additional findings from this work suggest that the molecular characteristics mediating APC activation are not limited to hydrophobicity but vary in complexity (e.g., presentation of oxygen-rich molecular patterns to cells) and elicit unique patterns of cellular activation. The approach outlined herein demonstrates the ability to rationally design pathogen-mimicking nanoparticle adjuvants for use in next-generation vaccines against emerging and re-emerging diseases.

Rational design of pathogen-mimicking amphiphilic materials as nanoadjuvants.

An opportunity exists today for cross-cutting research utilizing advances in materials science, immunology, microbial pathogenesis, and computational analysis to effectively design the next generation of adjuvants and vaccines. This study integrates these advances into a bottom-up approach for the molecular design of nanoadjuvants capable of mimicking the immune response induced by a natural infection but without the toxic side effects. Biodegradable amphiphilic polyanhydrides possess the unique ability to mimic pathogens and pathogen associated molecular patterns with respect to persisting within and activating immune cells, respectively. The molecular properties responsible for the pathogen-mimicking abilities of these materials have been identified. The value of using polyanhydride nanovaccines was demonstrated by the induction of long-lived protection against a lethal challenge of Yersinia pestis following a single administration ten months earlier. This approach has the tantalizing potential to catalyze the development of next generation vaccines against diseases caused by emerging and re-emerging pathogens.