ArticleJournal of proteome research2021
Improved SILAC Quantification with Data-Independent Acquisition to Investigate Bortezomib-Induced Protein Degradation.
Article in Journal of proteome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 67 citations in OpenAlex.
- AlphaDIA enables DIA transfer learning for feature-free proteomics.Nature biotechnology · 2026Article
- The proteomics and phosphoproteomics landscape of melanoma under T cell attack.Cell reports. Medicine · 2026Article
- Accurate quantification in proteomics with QuantUMS.Nature biotechnology · 2026Article
- The pursuit of ultrasensitive phosphoproteomics to unravel signalling in rare cells.Communications biology · 2025Review
- Plasma-Derived Extracellular Vesicle Proteomics.Journal of proteome research · 2025Review
- A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy.Nature communications · 2025Article
- Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025Review
- Time-Dependent Inhibition of Leucyl-tRNA-Synthetase (LeuRS): Insight into Target Vulnerability.ACS infectious diseases · 2025Article
- Data acquisition approaches for single cell proteomics.Proteomics · 2025Review
- Advancements in Single-Cell Proteomics and Mass Spectrometry-Based Techniques for Unmasking Cellular Diversity in Triple Negative Breast Cancer.Proteomics. Clinical applications · 2025Review
- Challenges of MS-based small extracellular vesicles proteomics.Journal of extracellular vesicles · 2024Review
- Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification.Molecular & cellular proteomics : MCP · 2024Article
- Instrumentation at the Leading Edge of Proteomics.Analytical chemistry · 2024Review
- Improved detection and consistency of RNA-interacting proteomes using DIA SILAC.Nucleic acids research · 2024Article
- In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development.Cell reports methods · 2024Article
- SILAC-based quantification reveals modulation of the immunopeptidome in BRAF and MEK inhibitor sensitive and resistant melanoma cells.Frontiers in immunology · 2024Article
- An integrated workflow for quantitative analysis of the newly synthesized proteome.Nature communications · 2023Article
- Identification and functional analysis of senescent cells in the cardiovascular system using omics approaches.American journal of physiology. Heart and circulatory physiology · 2023Review
- Modeling cell populations metabolism and competition under maximum power constraints.PLoS computational biology · 2023Article
- A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development.Molecular & cellular proteomics : MCP · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Stable isotope labeling by amino acids in cell culture (SILAC) coupled to data-dependent acquisition (DDA) is a common approach to quantitative proteomics with the desirable benefit of reducing batch effects during sample processing and data acquisition. More recently, using data-independent acquisition (DIA/SWATH) to systematically measure peptides has gained popularity for its comprehensiveness, reproducibility, and accuracy of quantification. The complementary advantages of these two techniques logically suggests combining them. Here we develop a SILAC-DIA-MS workflow using free, open-source software. We empirically determine that using DIA achieves similar peptide detection numbers as DDA and that DIA improves the quantitative accuracy and precision of SILAC by an order of magnitude. Finally, we apply SILAC-DIA-MS to determine protein turnover rates of cells treated with bortezomib, an FDA-approved 26S proteasome inhibitor for multiple myeloma and mantle cell lymphoma. We observe that SILAC-DIA produces more sensitive protein turnover models. Of the proteins determined to be differentially degraded by both acquisition methods, we find known proteins that are degraded by the ubiquitin-proteasome pathway, such as HNRNPK, EIF3A, and IF4A1/EIF4A-1, and a slower turnover for CATD, a protein implicated in invasive breast cancer. With improved quantification from DIA, we anticipate that this workflow will make SILAC-based experiments like protein turnover more sensitive.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.