A Compendium of Murine (Phospho)Peptides Encompassing Different Isobaric Labeling and Data Acquisition Strategies

Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics

Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.

Enriching Cysteine-Containing Peptides Using a Sulfhydryl-Reactive Alkylating Reagent with a Phosphonic Acid Group and Immobilized Metal Affinity Chromatography

The reduction of disulfide bonds and their subsequent alkylation are commonplace in typical proteomics workflows. Here, we highlight a sulfhydryl-reactive alkylating reagent with a phosphonic acid group (iodoacetamido-LC-phosphonic acid, 6C-CysPAT) that facilitates the enrichment of cysteine-containing peptides for isobaric tag-based proteome abundance profiling. Specifically, we profile the proteome of the SH-SY5Y human cell line following 24 h treatments with two proteasome inhibitors (bortezomib and MG-132) in a tandem mass tag (TMT)pro9-plex experiment. We acquire three datasets─(1) Cys-peptide enriched, (2) the unbound complement, and (3) the non-depleted control─and compare the peptides and proteins quantified in each dataset, with emphasis on Cys-containing peptides. The data show that enrichment using 6C-Cys phosphonate adaptable tag (6C-CysPAT) can quantify over 38,000 Cys-containing peptides in 5 h with >90% specificity. In addition, our combined dataset provides the research community with a resource of over 9900 protein abundance profiles exhibiting the effects of two different proteasome inhibitors. Overall, the seamless incorporation of alkylation by 6C-CysPAT into a current TMT-based workflow permits the enrichment of a Cys-containing peptide subproteome. The acquisition of this "mini-Cys" dataset can be used to preview and assess the quality of a deep, fractionated dataset.

A multi-purpose, regenerable, proteome-scale, human phosphoserine resource for phosphoproteomics

Mass-spectrometry-based phosphoproteomics has become indispensable for understanding cellular signaling in complex biological systems. Despite the central role of protein phosphorylation, the field still lacks inexpensive, regenerable, and diverse phosphopeptides with ground-truth phosphorylation positions. Here, we present Iterative Synthetically Phosphorylated Isomers (iSPI), a proteome-scale library of human-derived phosphoserine-containing phosphopeptides that is inexpensive, regenerable, and diverse, with precisely known positions of phosphorylation. We demonstrate possible uses of iSPI, including use as a phosphopeptide standard, a tool to evaluate and optimize phosphorylation-site localization algorithms, and a benchmark to compare performance across data analysis pipelines. We also present AScorePro, an updated version of the AScore algorithm specifically optimized for phosphorylation-site localization in higher energy fragmentation spectra, and the FLR viewer, a web tool for phosphorylation-site localization, to enable community use of the iSPI resource. iSPI and its associated data constitute a useful, multi-purpose resource for the phosphoproteomics community.

Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments

We present the first detailed study of chromatographic behavior of peptides labeled with tandem mass tags (TMT and TMTpro) in 2D LC for proteomic applications. Carefully designed experimental procedures have permitted generating data sets of over 100,000 nonlabeled and TMT-labeled peptide pairs for the low pH RP in the second separation dimension and data sets of over 10,000 peptide pairs for high-pH RP, HILIC (amide and silica), and SCX separations in the first separation dimension. The average increase in peptide RPLC (0.1% formic acid) retention upon TMT labeling was found to be 3.3% acetonitrile (linear water/acetonitrile gradients), spanning a range of -4 to 10.3%. In addition to the bulk peptide properties such as length, hydrophobicity, and the number of labeled residues, we found several sequence-dependent features mostly associated with differences in N-terminal chemistry. The behavior of TMTpro-labeled peptides was found to be very similar except for a slightly higher hydrophobicity: an average retention shift of 3.7% acetonitrile. The respective versions of the sequence-specific retention calculator (SSRCalc) model have been developed to accommodate both TMT chemistries, showing identical prediction accuracy (R² ∼ 0.98) for labeled and nonlabeled peptides. Higher retention for TMT-labeled peptides was observed for high-pH RP and HILIC separations, while SCX selectivity remained virtually unchanged.

Fe3+-NTA magnetic beads as an alternative to spin column-based phosphopeptide enrichment

Protein phosphorylation is a central mechanism of cellular signal transduction in living organisms. Phosphoproteomic studies systematically catalogue and characterize alterations in phosphorylation states across multiple cellular conditions and are often incorporated into global proteomics experiments. Previously, we found that spin column-based Fe³⁺-NTA enrichment integrated well with our workflow but remained a bottleneck for methods that require higher throughput or a scale that is beyond the capacity of these columns. Here, we compare our well-established spin column-based enrichment strategy with one encompassing magnetic beads. Our data show little difference when using either method in terms of the number of identified phosphopeptides as well as their physicochemical properties. In all, we illustrate how the potentially scalable and automation-friendly magnetic Fe³⁺-NTA beads can seamlessly substitute spin column-based Fe³⁺-NTA agarose beads for global phosphoproteome profiling. SIGNIFICANCE: Protein phosphorylation plays a key role in regulating a multitude of biological processes and can lead to insights into disease pathogenesis. Methodologies which can efficiently enrich phosphopeptides in a scalable and high-throughput manner are essential for profiling dynamic phosphoproteomes. Here we compare two phosphopeptide enrichment workflows, a well-established spin column-based strategy with agarose Fe³⁺-NTA beads and a strategy using magnetic Fe³⁺-NTA beads. Our data suggest that the scalable and automation-friendly magnetic bead-based workflow is an equivalent, but more flexible, enrichment strategy for phosphoproteome profiling experiments.

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.