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| Item Type: | Article |
|---|---|
| Title: | Combining Data Independent Acquisition with spike-in SILAC (DIA-SiS) improves proteome coverage and quantification |
| Creators Name: | Welter, A.S., Gerwien, M., Kerridge, R., Alp, K.M., Mertins, P. and Selbach, M. |
| 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 and certain high-throughput experiments. 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 DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces 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. |
| Keywords: | Amino Acids, Isotope Labeling, Proteome, Proteomics, Tandem Mass Spectrometry / Methods, Animals, Mice |
| Source: | Molecular & Cellular Proteomics |
| ISSN: | 1535-9484 |
| Publisher: | American Society for Biochemistry and Molecular Biology |
| Volume: | 23 |
| Number: | 10 |
| Page Range: | 100839 |
| Date: | October 2024 |
| Official Publication: | https://doi.org/10.1016/j.mcpro.2024.100839 |
| PubMed: | View item in PubMed |
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