Systematic detection of functional proteoform groups from bottom-up proteomic datasets

Isabell Bludau, Max Frank, Christian Dörig, Yujia Cai, Moritz Heusel, George Rosenberger, Paola Picotti, Ben C. Collins, Hannes Röst () and Ruedi Aebersold ()
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Isabell Bludau: Institute of Molecular Systems Biology, ETH Zurich
Max Frank: Institute of Molecular Systems Biology, ETH Zurich
Christian Dörig: Institute of Molecular Systems Biology, ETH Zurich
Yujia Cai: University of Toronto
Moritz Heusel: Institute of Molecular Systems Biology, ETH Zurich
George Rosenberger: Institute of Molecular Systems Biology, ETH Zurich
Paola Picotti: Institute of Molecular Systems Biology, ETH Zurich
Ben C. Collins: Institute of Molecular Systems Biology, ETH Zurich
Hannes Röst: University of Toronto
Ruedi Aebersold: Institute of Molecular Systems Biology, ETH Zurich

Nature Communications, 2021, vol. 12, issue 1, 1-18

Abstract: 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 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.

Date: 2021
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DOI: 10.1038/s41467-021-24030-x

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