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PXD052080

PXD052080 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleCombining data independent acquisition with spike-in SILAC (DIA-SiS) improves proteome coverage and quantification )
DescriptionData Independent Acquisition (DIA) is increasingly preferred over Data Dependent Acquisition (DDA) due to its higher throughput and fewer missing values. Whereas DDA often utilizes stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mTRAQ and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios. Spike-in SILAC methods utilize an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA with spike-in SILAC (DIA-SiS), leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed and rigorously validated DIA-SiS through a mixed-species benchmark to assess its performance in proteome coverage and quantification. We demonstrate that DIA-SiS significantly improves proteome coverage and quantification compared to label-free approaches and reduces the incidence of incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded (FFPE) tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate and comprehensive proteome profiling.
HostingRepositoryPRIDE
AnnounceDate2024-10-15
AnnouncementXMLSubmission_2024-10-15_01:50:10.706.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterMaximilian Gerwien
SpeciesList scientific name: Escherichia coli; NCBI TaxID: 562; scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListNo PTMs are included in the dataset
InstrumentOrbitrap Exploris 480; timsTOF Pro 2
Dataset History
RevisionDatetimeStatusChangeLog Entry
02024-05-07 08:51:54ID requested
12024-10-15 01:50:12announced
Publication List
Welter AS, Gerwien M, Kerridge R, Alp KM, Mertins P, Selbach M, Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification. Mol Cell Proteomics, 23(10):100839(2024) [pubmed]
10.1016/j.mcpro.2024.100839;
Keyword List
submitter keyword: Multiplexing, DIA, PlexDIA,SILAC, Proteomics, Benchmark
Contact List
Matthias Selbach
contact affiliationMax Delbrück Center for Molecular Medicine Berlin and Charite Berlin
contact emailmatthias.selbach@mdc-berlin.de
lab head
Maximilian Gerwien
contact affiliationMDC Berlin
contact emailmaximilian.gerwien@mdc-berlin.de
dataset submitter
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Dataset FTP location
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