DiagnoTop

DiagnoTop identifies and differentiates bacterial pathogens from top-down proteomics (TDP) data by detecting discriminative proteoform spectral clusters without relying on database searches.


Key Features:

  • Database-free identification: Operates without database searches to enable analysis of poorly annotated microbial proteomes.
  • Top-down proteomics input: Processes top-down proteomics (TDP) mass spectra and TDP datasets, including enterobacterial TDP datasets.
  • Proteoform-focused analysis: Detects species-unique proteoforms and uses them as discriminative signals.
  • Discriminative spectral cluster detection: Identifies, lists, and shortlists discriminative spectral clusters and high-quality spectra.
  • Differentiation of closely related enterobacteria: Resolves species-level ambiguity among Escherichia coli, Shigella, and Salmonella using discriminative clusters.
  • Diagnostic and biomarker potential: Enhances diagnostic power and supports biomarker discovery from TDP-derived proteoform signatures.

Scientific Applications:

  • Clinical pathogen identification: Confirming bacterial infections to inform antimicrobial therapy decisions.
  • Differentiation of enterobacterial pathogens: Resolving taxonomic ambiguity among Escherichia coli, Shigella, and Salmonella in mass-spectrometry-based analyses.
  • Biomarker discovery: Identifying species-specific proteoform signatures from top-down proteomics data.
  • Analysis of poorly annotated proteomes: Enabling proteomic studies where reference databases are incomplete or lacking annotations.

Methodology:

Analyzes top-down proteomics (TDP) mass spectra to detect, list, and shortlist discriminative spectral clusters and proteoforms without performing database searches.

Topics

Details

Tool Type:
desktop application, workflow
Added:
9/8/2021
Last Updated:
9/13/2021

Operations

Publications

Borges Lima D, Dupré M, Mariano Santos MD, Carvalho PC, Chamot-Rooke J. DiagnoTop: A Computational Pipeline for Discriminating Bacterial Pathogens without Database Search. Journal of the American Society for Mass Spectrometry. 2021;32(6):1295-1299. doi:10.1021/jasms.1c00014. PMID:33856212.

PMID: 33856212
Funding: - Agence Nationale de la Recherche: ANR-15-CE18-0021 - H2020 Research Infrastructures: 823839 - H2020 Health: 773830

Documentation