SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles
Moritz Heusel, Isabell Bludau, Ben C. Collins, Claudia Martelli, Evan G. Williams, Peng Xue, Yansheng Liu, Ruedi Aebersold, Andrea Califano
Abstract
Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state.
附件下载：
SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles, Cell Syst, 16 Dec 2020
Cell Systems, 16 December, 2020, DOI：https://doi.org/10.1016/j.cels.2020.11.006
SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles
Moritz Heusel, Isabell Bludau, Ben C. Collins, Claudia Martelli, Evan G. Williams, Peng Xue, Yansheng Liu, Ruedi Aebersold, Andrea Califano
Abstract
Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state.
文章链接：https://www.cell.com/cell-systems/fulltext/S2405-4712(20)30457-9?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405471220304579%3Fshowall%3Dtrue