Molecular determinants of T cell epitope recognition to the common Timothy grass allergen.

We investigated the molecular determinants of allergen-derived T cell epitopes in humans utilizing the Phleum pratense (Timothy grass) allergens (Phl p). PBMCs from allergic individuals were tested in ELISPOT assays with overlapping peptides spanning known Phl p allergens. A total of 43 distinct antigenic regions were recognized, illustrating the large breadth of grass-specific T cell epitopes. Th2 cytokines (as represented by IL-5) were predominant, whereas IFN-gamma, IL-10, and IL-17 were detected less frequently. Responses from specific immunotherapy treatment individuals were weaker and less consistent, yet similar in epitope specificity and cytokine pattern to allergic donors, whereas nonallergic individuals were essentially nonreactive. Despite the large breadth of recognition, nine dominant antigenic regions were defined, each recognized by multiple donors, accounting for 51% of the total response. Multiple HLA molecules and loci restricted the dominant regions, and the immunodominant epitopes could be predicted using bioinformatic algorithms specific for 23 common HLA-DR, DP, and DQ molecules. Immunodominance was also apparent at the Phl p Ag level. It was found that 52, 19, and 14% of the total response was directed to Phl p 5, 1, and 3, respectively. Interestingly, little or no correlation between Phl p-specific IgE levels and T cell responses was found. Thus, certain intrinsic features of the allergen protein might influence immunogenicity at the level of T cell reactivity. Consistent with this notion, different Phl p Ags were associated with distinct patterns of IL-5, IFN-gamma, IL-10, and IL-17 production.

IMMUNOCAT-a data management system for epitope mapping studies.

To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established "IMMUNOCAT", an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

TiArA: a virtual appliance for the analysis of Tiling Array data.

BACKGROUND: Genomic tiling arrays have been described in the scientific literature since 2003, yet there is a shortage of user-friendly applications available for their analysis. METHODOLOGY/PRINCIPAL FINDINGS: Tiling Array Analyzer (TiArA) is a software program that provides a user-friendly graphical interface for the background subtraction, normalization, and summarization of data acquired through the Affymetrix tiling array platform. The background signal is empirically measured using a group of nonspecific probes with varying levels of GC content and normalization is performed to enforce a common dynamic range. CONCLUSIONS/SIGNIFICANCE: TiArA is implemented as a standalone program for Linux systems and is available as a cross-platform virtual machine that will run under most modern operating systems using virtualization software such as Sun VirtualBox or VMware. The software is available as a Debian package or a virtual appliance at http://purl.org/NET/tiara.