K-TOPE
K-TOPE identifies antibody-binding epitopes within proteins and proteomes by analyzing next-generation sequencing data from antibody-selected peptide libraries to characterize antibody specificity.
Key Features:
- Generalizable strategy: Analyzes next-generation sequencing data from randomly selected antibody-binding peptides across 273 distinct sera and is applicable to both monoclonal and polyclonal antibodies.
- K-mer tiling technique: Tiles candidate antigen sequences into short overlapping k-mers and measures k-mer enrichment in the antibody-binding peptide dataset relative to background to pinpoint potential epitopes.
- Validation and accuracy: Recovers known epitopes targeted by antibodies with characterized specificity as a positive control.
- Broad proteome application: Applied to 2,908 proteins from 400 viral taxa infecting humans to identify epitopes recognized across specimens, including enteroviruses, Epstein-Barr virus, Staphylococcus, and Streptococcus.
- Consistency with mapped epitopes: Identified common viral and bacterial epitopes that agree with previously mapped epitopes.
- Pathogen discrimination: Detects pathogen-specific epitopes, including 30 HSV2-specific epitopes that are specific against HSV1.
Scientific Applications:
- Immune repertoire mapping: Characterizes antibody epitope specificities within individual sera and across cohorts to profile humoral responses.
- Vaccine antigen discovery: Prioritizes antigenic epitopes across proteomes for vaccine development.
- Serodiagnostics and biomarker discovery: Identifies pathogen- and disease-specific epitopes to inform diagnostic assay and biomarker development.
- Pathogen-specific discrimination: Enables discrimination of closely related pathogens through species- or strain-specific epitope identification (e.g., HSV2 versus HSV1).
Methodology:
Use next-generation sequencing data from randomly selected antibody-binding peptides across 273 sera; tile candidate antigen sequences into overlapping k-mers and compute k-mer enrichment relative to background to identify putative epitopes.
Topics
Details
- License:
- MIT
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java, Python
- Added:
- 8/9/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Paull ML, Johnston T, Ibsen KN, Bozekowski JD, Daugherty PS. A general approach for identifying protein epitopes targeted by antibody repertoires using whole proteomes. Unknown Journal. 2019. doi:10.1101/641787.
DOI: 10.1101/641787
Documentation
Links
Issue tracker
https://github.com/mlpaull/KTOPE/issues