HSPVdb--the Human Short Peptide Variation Database for improved mass spectrometry-based detection of polymorphic...

Area of Science:

• Immunology
• Proteomics
• Bioinformatics

Background:

• T cell epitopes from polymorphic proteins and alternative reading frames (ARFs) are crucial in tumor immunology.
• Current mass spectrometry approaches struggle with identifying these epitopes due to limitations in standard protein databases.

Purpose of the Study:

• To create a specialized database for identifying polymorphic T cell epitopes.
• To enhance the accuracy of mass spectrometry-based T cell epitope discovery.

Main Methods:

• Developed the Human Short Peptide Variation Database (HSPVdb) using human mRNA sequences (RefSeq) and single nucleotide polymorphism (SNP) data (dbSNP).
• Removed non-polymorphic sequences and non-polymorphic "SNPs" to create a high-quality, focused dataset.
• Validated the database using mass spectrometry data.

Main Results:

• The HSPVdb successfully identified the majority of previously published polymorphic SNP- and/or ARF-derived epitopes.
• The database facilitated the identification of diverse polymorphic peptides within the HLA-ligandome of Epstein-Barr virus-infected cells.

Conclusions:

• The HSPVdb is a valuable resource for mass spectrometry-based identification of polymorphic T cell epitopes.
• This database significantly improves the discovery of T cell epitopes relevant to tumor immunology and infectious diseases.