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.

Documentation

Links