Improved SILAC Quantification with Data-Independent Acquisition to Investigate Bortezomib-Induced Protein Degradation

Stable isotope labeling by amino acids in cell culture (SILAC) coupled to data-dependent acquisition (DDA) is a common approach quantitative proteomics with the desirable benefit of reducing batch effects during sample processing and data acquisition. More recently, using data-independent (DIA/SWATH) systematically measure peptides has gained popularity for its comprehensiveness, reproducibility, accuracy quantification. The complementary advantages these two techniques logically suggests combining them. Here we develop SILAC-DIA-MS workflow free, open-source software. We empirically determine that DIA achieves similar peptide detection numbers as DDA improves precision SILAC an order magnitude. Finally, apply protein turnover rates cells treated bortezomib, FDA-approved 26S proteasome inhibitor multiple myeloma mantle lymphoma. observe SILAC-DIA produces more sensitive models. Of proteins determined be differentially degraded both methods, find known are ubiquitin-proteasome pathway, such HNRNPK, EIF3A, IF4A1/EIF4A-1, slower CATD, implicated invasive breast cancer. With improved quantification from DIA, anticipate this will make SILAC-based experiments like sensitive.