Systematic detection of functional proteoform groups from bottom-up proteomic datasets
(2021) In Nature Communications 12(1).- Abstract
To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene – so-called proteoforms – that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation... (More)
To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene – so-called proteoforms – that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation data as well as to more typical protein abundance vs. sample data matrices, demonstrating the systematic detection of assembly- and tissue-specific proteoform groups, respectively, in either dataset. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets.
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- author
- Bludau, Isabell ; Frank, Max ; Dörig, Christian ; Cai, Yujia ; Heusel, Moritz LU ; Rosenberger, George ; Picotti, Paola ; Collins, Ben C. ; Röst, Hannes and Aebersold, Ruedi
- organization
- publishing date
- 2021-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Communications
- volume
- 12
- issue
- 1
- article number
- 3810
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:34155216
- scopus:85108404338
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-021-24030-x
- language
- English
- LU publication?
- yes
- id
- ff52fc6e-55a9-49c8-b37f-35deee182454
- date added to LUP
- 2021-12-23 14:00:44
- date last changed
- 2024-04-20 18:18:23
@article{ff52fc6e-55a9-49c8-b37f-35deee182454,
abstract = {{<p>To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene – so-called proteoforms – that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation data as well as to more typical protein abundance vs. sample data matrices, demonstrating the systematic detection of assembly- and tissue-specific proteoform groups, respectively, in either dataset. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets.</p>}},
author = {{Bludau, Isabell and Frank, Max and Dörig, Christian and Cai, Yujia and Heusel, Moritz and Rosenberger, George and Picotti, Paola and Collins, Ben C. and Röst, Hannes and Aebersold, Ruedi}},
issn = {{2041-1723}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Nature Communications}},
title = {{Systematic detection of functional proteoform groups from bottom-up proteomic datasets}},
url = {{http://dx.doi.org/10.1038/s41467-021-24030-x}},
doi = {{10.1038/s41467-021-24030-x}},
volume = {{12}},
year = {{2021}},
}