To date, the effects of specific modification types and sites on protein lifetime have not been systematically illustrated. Here, we describe a proteomic method, DeltaSILAC, to quantitatively assess the impact of site-specific phosphorylation on the turnover of thousands of proteins in live cells. Based on the accurate and reproducible mass spectrometry-based method, a pulse labeling approach using stable isotope-labeled amino acids in cells (pSILAC), phosphoproteomics, and a unique peptide-level matching strategy, our DeltaSILAC profiling revealed a global, unexpected delaying effect of many phosphosites on protein turnover. We further found that phosphorylated sites accelerating protein turnover are functionally selected for cell fitness, enriched in Cyclin-dependent kinase substrates, and evolutionarily conserved, whereas the glutamic acids surrounding phosphosites significantly delay protein turnover. Our method represents a generalizable approach and provides a rich resource for prioritizing the effects of phosphorylation sites on protein lifetime in the context of cell signaling and disease biology.

• Keywords
• DeltaSILAC, data-independent acquisition, mass spectrometry, phosphomodiform, phosphorylation, protein lifetime, protein turnover, proteomics, pulse SILAC,
• MeSH
• Cell Cycle physiology   MeSH
• Cyclin-Dependent Kinases genetics   metabolism   MeSH
• Phosphoproteins chemistry   metabolism   MeSH
• Phosphorylation MeSH
• Glutamates metabolism   MeSH
• Mass Spectrometry methods   MeSH
• Isotope Labeling methods   MeSH
• Humans MeSH
• Cell Line, Tumor MeSH
• Peptides metabolism   MeSH
• Peroxiredoxin VI chemistry   metabolism   MeSH
• Proteolysis * MeSH
• Proteome genetics   metabolism   MeSH
• Proteomics methods   MeSH
• Amino Acid Sequence MeSH
• RNA Splicing Factors chemistry   metabolism   MeSH
• Signal Transduction genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Cyclin-Dependent Kinases MeSH
• Phosphoproteins MeSH
• Glutamates MeSH
• Peptides MeSH
• Peroxiredoxin VI MeSH
• PRDX6 protein, human MeSH Browser
• Proteome MeSH
• RNA Splicing Factors MeSH
• SF3B1 protein, human MeSH Browser

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post-translational turnover, we devised a strategy combining pulse stable isotope-labeled amino acids in cells (pSILAC), data-independent acquisition mass spectrometry (DIA-MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome-wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.

• Keywords
• DIA mass spectrometry, alternative splicing, protein turnover, proteomics, pulsed SILAC,
• MeSH
• Alternative Splicing MeSH
• HeLa Cells MeSH
• Mass Spectrometry MeSH
• RNA Isoforms genetics   metabolism   MeSH
• Isotope Labeling methods   MeSH
• Humans MeSH
• RNA, Messenger genetics   metabolism   MeSH
• Protein Isoforms analysis   metabolism   MeSH
• Proteins analysis   metabolism   MeSH
• Proteolysis MeSH
• Proteomics methods   MeSH
• Workflow MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• RNA Isoforms MeSH
• RNA, Messenger MeSH
• Protein Isoforms MeSH
• Proteins MeSH

Due to the technical advances of mass spectrometers, particularly increased scanning speed and higher MS/MS resolution, the use of data-independent acquisition mass spectrometry (DIA-MS) became more popular, which enables high reproducibility in both proteomic identification and quantification. The current DIA-MS methods normally cover a wide mass range, with the aim to target and identify as many peptides and proteins as possible and therefore frequently generate MS/MS spectra of high complexity. In this report, we assessed the performance and benefits of using small windows with, e.g., 5-m/z width across the peptide elution time. We further devised a new DIA method named RTwinDIA that schedules the small isolation windows in different retention time blocks, taking advantage of the fact that larger peptides are normally eluting later in reversed phase chromatography. We assessed the direct proteomic identification by using shotgun database searching tools such as MaxQuant and pFind, and also Spectronaut with an external comprehensive spectral library of human proteins. We conclude that algorithms like pFind have potential in directly analyzing DIA data acquired with small windows, and that the instrumental time and DIA cycle time, if prioritized to be spent on small windows rather than on covering a broad mass range by large windows, will improve the direct proteome coverage for new biological samples and increase the quantitative precision. These results further provide perspectives for the future convergence between DDA and DIA on faster MS analyzers.

• Keywords
• Data-independent acquisition, Isolation windows, Maxquant, Spectronaut, pFind,
• MeSH
• Chromatography, Reverse-Phase MeSH
• Mass Spectrometry methods   MeSH
• Humans MeSH
• Cell Line, Tumor MeSH
• Peptides analysis   MeSH
• Proteins analysis   MeSH
• Proteomics methods   MeSH
• Software MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Peptides MeSH
• Proteins MeSH