Human CD4+ T Cell Epitopes from Vaccinia Virus Induced by Vaccination or Infection

Despite the importance of vaccinia virus in basic and applied immunology, our knowledge of the human immune response directed against this virus is very limited. CD4+ T cell responses are an important component of immunity induced by current vaccinia-based vaccines, and likely will be required for new subunit vaccine approaches, but to date vaccinia-specific CD4+ T cell responses have been poorly characterized, and CD4+ T cell epitopes have been reported only recently. Classical approaches used to identify T cell epitopes are not practical for large genomes like vaccinia. We developed and validated a highly efficient computational approach that combines prediction of class II MHC-peptide binding activity with prediction of antigen processing and presentation. Using this approach and screening only 36 peptides, we identified 25 epitopes recognized by T cells from vaccinia-immune individuals. Although the predictions were made for HLA-DR1, eight of the peptides were recognized by donors of multiple haplotypes. T cell responses were observed in samples of peripheral blood obtained many years after primary vaccination, and were amplified after booster immunization. Peptides recognized by multiple donors are highly conserved across the poxvirus family, including variola, the causative agent of smallpox, and may be useful in development of a new generation of smallpox vaccines and in the analysis of the immune response elicited to vaccinia virus. Moreover, the epitope identification approach developed here should find application to other large-genome pathogens

Using graph grammar systems with memory in computer aided design

Any design problem can be treated as a cooperative task involving many different tasks and requirements that have to be satisfied in order to produce a final design. Each participant, which can be seen as an agent contributes its knowledge and abilities to the common goal. This paper deals with an approach based on graph grammar model of cooperation and distribution for generating designs in computer aided design domain. Each design is represented as a graph. Thus each agent is equipped with its own set of rules (a graph grammar) enabling it to add to the design. The motivation for the idea presented is given and some possible modes of application are briefly described

Generating a virtual computational grid by graph transformations

This chapter aims at contributing to a better understanding of generation and simulation problems of the grid. Towards this end, we propose a new graph structure called layered graphs. This approach enables us to use attributed graph grammars as a tool to generate at the same time both a grid structure and its parameters. To illustrate our method an example of a grid generated by means of graph grammar rules is presented. The obtained results allow us to investigate properties of a grid in a more general way

Vaccinia peptides eluted from HLA-DR1 isolated from virus-infected cells are recognized by CD4+ T cells from a vaccinated donor

Class II MHC proteins bind peptides and present them to CD4 (+) T cells as part of the immune system\u27s surveillance of bodily tissues for foreign and pathogenic material. Antigen processing and presentation pathways have been characterized in detail in normal cells, but there is little known about the actual viral peptides that are presented to CD4 (+) T cells that signal infection. In this study, two-dimensional LC-MS/MS was used to identify vaccinia virus-derived peptides among the hundreds to thousands of peptide antigens bound to the human class II MHC protein HLA-DR1 on the surface of vaccinia virus-infected cells. The peptides, derived from the I6L, D6R, and A10L viral proteins, were 15 residues in length, bound efficiently to HLA-DR1 as synthetic peptides, and were recognized by vaccinia-specific CD4 (+) T cells obtained from an immunized donor