TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data.
Proteomics
; 24(19): e2300491, 2024 Oct.
Article
en En
| MEDLINE
| ID: mdl-39126236
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 enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "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 TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR 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 TermineR approach and example data are available as an R package at https//github.com/MiguelCos/TermineR.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Proteómica
/
Espectrometría de Masas en Tándem
/
Proteolisis
Límite:
Animals
Idioma:
En
Revista:
Proteomics
Asunto de la revista:
BIOQUIMICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Alemania