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PXD055943-1

PXD055943 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleCombining quantitative proteomics and interactomics for a deeper insight into molecular differences between human cell lines
DescriptionCellular functional pathways have evolved through selection based on fitness benefits conferred through protein intra- and inter-molecular interactions that comprise all protein conformational features and protein-protein interactions, collectively referred to as the interactome. While the interactome is regulated by proteome levels, it is also regulated independently by, post translational modification, co-factor, and ligand levels, as well as local protein environmental factors, such as osmolyte concentration, pH, ionic strength, temperature and others. In modern biomedical research, cultivatable cell lines have become an indispensable tool, with selection of optimal cell lines that exhibit specific functional profiles being critical for success in many cases. While it is clear that cell lines derived from different cell types have differential proteome levels, increased understanding of large-scale functional differences requires additional information beyond abundance level measurements, including how protein conformations and interactions are altered in certain cell types to shape functional landscapes. Here, we employed quantitative in vivo protein cross-linking coupled to mass spectrometry to probe large-scale protein conformational and interaction changes among three commonly employed human cell lines, HEK293, MCF-7, and HeLa cells. Isobaric quantitative Protein Interaction Reporter (iqPIR) technologies were used to obtain quantitative values of cross-linked peptides across three cell lines. These data illustrated highly reproducible (R2 values larger than 0.8 for all biological replicates) quantitative interactome levels across multiple biological replicates. We also measured protein abundance levels in these cells using data independent acquisition quantitative proteomics methods. Combining quantitative interactome and proteomics information allowed visualization of cell type-specific interactome changes mediated by proteome level adaptations as well as independently regulated interactome changes to gain deeper insight into possible drivers of these changes. Among the biggest detected alterations in protein interactions and conformations are changes in cytoskeletal proteins, RNA-binding proteins, chromatin remodeling complexes, mitochondrial proteins, and others. Overall, these data demonstrate the utility and reproducibility of quantitative cross-linking to study systems-level interactome variations. Moreover, these results illustrate how combined quantitative interactomics and proteomics can provide unique insight on cellular functional landscapes.
HostingRepositoryPRIDE
AnnounceDate2024-09-17
AnnouncementXMLSubmission_2024-09-17_09:32:58.113.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterAnna Bakhtina
SpeciesList scientific name: Mus musculus (Mouse); NCBI TaxID: 10090;
ModificationListmonohydroxylated residue; iodoacetamide derivatized residue
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02024-09-17 08:45:54ID requested
12024-09-17 09:32:58announced
22024-10-22 06:58:55announced2024-10-22: Updated project metadata.
Publication List
Dataset with its publication pending
Keyword List
submitter keyword: mouse, cross-linking, mitochondria
Contact List
Jim Bruce
contact affiliationDepartment of Genome Sciences, University of Washington
contact emailjimbruce@uw.edu
lab head
Anna Bakhtina
contact affiliationUniversity of Washington
contact emailanna.bakhtina91@gmail.com
dataset submitter
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Dataset FTP location
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