BIITE: A Tool to Determine HLA Class II Epitopes from T Cell ELISpot Data

Area of Science:

• Immunology
• Computational Biology
• Bioinformatics

Background:

• CD4+ T cell activation relies on peptides presented by HLA class II molecules, often assessed via ELISpot assays.
• Determining specific HLA class II:peptide interactions responsible for positive ELISpot responses is complex due to multiple HLA class II molecules and unclear binding motifs.

Purpose of the Study:

• To develop a Bayesian framework, BIITE (Bayesian Immunogenicity Inference Tool for ELISpot), for interpreting ELISpot data.
• To identify immunogenic HLA-II:peptide combinations using cohort ELISpot data.

Main Methods:

• A novel Bayesian framework (BIITE) was developed to analyze ELISpot assay results.
• The BIITE tool was applied to existing ELISpot datasets and validated using simulations.

Main Results:

• BIITE demonstrated high accuracy in identifying immunogenic HLA-II:peptide combinations.
• Method performance is influenced by cohort size and ELISpot assay success rates.

Conclusions:

• BIITE provides a robust computational approach to interpret complex ELISpot data.
• This tool can significantly aid in understanding T cell immunogenicity and HLA class II associations.