Proteomics

Dataset Information

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Combining data independent acquisition with spike-in SILAC (DIA-SiS) improves proteome coverage and quantification )


ABSTRACT: Data 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.

INSTRUMENT(S): timsTOF Pro 2, Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

TISSUE(S): Cell Suspension Culture, Cell Culture

SUBMITTER: Maximilian Gerwien  

LAB HEAD: Matthias Selbach

PROVIDER: PXD052080 | Pride | 2024-10-14

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20230125_uniprot_ecoli_reference_speciesInfo.fasta Fasta
20230125_uniprot_human_reference_speciesInfo.fasta Fasta
FFPE_output_LF_L300H0.tar Other
FFPE_output_LF_L50H0.tar Other
FFPE_output_spikein_L50H250.tar Other
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Publications

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification.

Welter Anna Sophie AS   Gerwien Maximilian M   Kerridge Robert R   Alp Keziban Merve KM   Mertins Philipp P   Selbach Matthias M  

Molecular & cellular proteomics : MCP 20240911 10


Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample prepa  ...[more]

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