Peptide Correlation Analysis (PeCorA) Reveals Differential Proteoform Regulation.
J Proteome Res
; 20(4): 1972-1980, 2021 04 02.
Article
in English
| MEDLINE | ID: covidwho-978492
ABSTRACT
Shotgun proteomics techniques infer the presence and quantity of proteins using peptide proxies produced by cleavage of the proteome with a protease. Most protein quantitation strategies assume that multiple peptides derived from a protein will behave quantitatively similar across treatment groups, but this assumption may be false due to (1) heterogeneous proteoforms and (2) technical artifacts. Here we describe a strategy called peptide correlation analysis (PeCorA) that detects quantitative disagreements between peptides mapped to the same protein. PeCorA fits linear models to assess whether a peptide's change across treatment groups differs from all other peptides assigned to the same protein. PeCorA revealed that â¼15% of proteins in a mouse microglia stress data set contain at least one discordant peptide. Inspection of the discordant peptides shows the utility of PeCorA for the direct and indirect detection of regulated post-translational modifications (PTMs) and also for the discovery of poorly quantified peptides. The exclusion of poorly quantified peptides before protein quantity summarization decreased false-positives in a benchmark data set. Finally, PeCorA suggests that the inactive isoform of prothrombin, a coagulation cascade protease, is more abundant in plasma from COVID-19 patients relative to non-COVID-19 controls. PeCorA is freely available as an R package that works with arbitrary tables of quantified peptides.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Peptides
/
Proteomics
Type of study:
Experimental Studies
/
Randomized controlled trials
Limits:
Animals
/
Humans
Language:
English
Journal:
J Proteome Res
Journal subject:
Biochemistry
Year:
2021
Document Type:
Article
Affiliation country:
Acs.jproteome.0c00602
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