loading page

Fragterminomics: extracting information on proteolytic processing from shotgun proteomics data processed by FragPipe
  • +12
  • Miguel Cosenza-Contreras,
  • Adrianna Seredynska,
  • Niko Pinter,
  • Eva Brombacher,
  • Thien-Ly Julia Dinh,
  • Patrick Bernhard,
  • Manuel Rogg,
  • Junwei Liu,
  • Patrick Willems,
  • Simon Stael,
  • Pitter Huesgen,
  • E. Wolfgang Kuehn,
  • Clemens Kreutz,
  • Christoph Schell,
  • Oliver Schilling
Miguel Cosenza-Contreras
University Medical Center Freiburg Institute of Pathology
Author Profile
Adrianna Seredynska
University Medical Center Freiburg Institute of Pathology
Author Profile
Niko Pinter
University Medical Center Freiburg Institute of Pathology
Author Profile
Eva Brombacher
University of Freiburg Faculty of Biology
Author Profile
Thien-Ly Julia Dinh
University Medical Center Freiburg Institute of Pathology
Author Profile
Patrick Bernhard
University Medical Center Freiburg Institute of Pathology
Author Profile
Manuel Rogg
University Medical Center Freiburg Institute of Pathology
Author Profile
Junwei Liu
Faculty of Medicine, Medical Center - University of Freiburg
Author Profile
Patrick Willems
Ghent University Department of Biomolecular Medicine
Author Profile
Simon Stael
VIB-UGENT Center for Plant Systems Biology
Author Profile
Pitter Huesgen
Forschungszentrum Jülich
Author Profile
E. Wolfgang Kuehn
Department of Medicine IV, Faculty of Medicine, Medical Center - University of Freiburg
Author Profile
Clemens Kreutz
Centre for Integrative Biological Signaling (CIBSS)
Author Profile
Christoph Schell
University Medical Center Freiburg Institute of Pathology
Author Profile
Oliver Schilling
University Medical Center Freiburg Institute of Pathology

Corresponding Author:oliver.schilling@mol-med.uni-freiburg.de

Author Profile

Abstract

State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforces a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify native protein termini or those arising from endogenous proteolytic activity (also referred to ‘neo-N-termini’ analysis or ‘N-terminomics’. Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce Fragterminomics, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, (3) visualization of neo-N-termini location, and (4) mapping neo-N-termini to known protein processing features. We illustrate the use of Fragterminomics by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The Fragterminomics approach and example data are available as an R package at https://github.com/MiguelCos/Fragterminomics.
31 Oct 2023Submitted to PROTEOMICS
03 Nov 2023Submission Checks Completed
03 Nov 2023Assigned to Editor
03 Nov 2023Review(s) Completed, Editorial Evaluation Pending
03 Nov 2023Reviewer(s) Assigned
10 Jul 2024Review(s) Completed, Editorial Evaluation Pending
10 Jul 2024Editorial Decision: Accept