Gas-Phase Rearrangements Do Not Affect Site Localization Reliability in Phosphoproteomics Data Sets

Intramolecular transfer of phosphate during collision-induced dissociation (CID) in ion-trap mass spectrometers has recently been described. Because phosphorylation events are assigned to discrete serine, threonine, and tyrosine residues based on the presence of site-determining ions in MS/MS spectra, phosphate transfer may invalidate or confound site localization in published large-scale phosphorylation data sets. Here, we present evidence for the occurrence of this phenomenon using synthetic phosphopeptide libraries, specifically for doubly charged species. We found, however, that the extent of the transfer reaction was insufficient to cause localization of phosphorylation sites to incorrect residues. We further compared CID to electron-transfer dissociation (ETD) for site localization using synthetic libraries and a large-scale yeast phosphoproteome experiment. The agreement in site localization was >99.5 and 93%, respectively, suggesting that ETD-based site localization is no more reliable than CID. We conclude that intramolecular phosphate transfer does not affect the reliability of current or past phosphorylation data sets

Gas-Phase Rearrangements Do Not Affect Site Localization Reliability in Phosphoproteomics Data Sets

Intramolecular transfer of phosphate during collision-induced dissociation (CID) in ion-trap mass spectrometers has recently been described. Because phosphorylation events are assigned to discrete serine, threonine, and tyrosine residues based on the presence of site-determining ions in MS/MS spectra, phosphate transfer may invalidate or confound site localization in published large-scale phosphorylation data sets. Here, we present evidence for the occurrence of this phenomenon using synthetic phosphopeptide libraries, specifically for doubly charged species. We found, however, that the extent of the transfer reaction was insufficient to cause localization of phosphorylation sites to incorrect residues. We further compared CID to electron-transfer dissociation (ETD) for site localization using synthetic libraries and a large-scale yeast phosphoproteome experiment. The agreement in site localization was >99.5 and 93%, respectively, suggesting that ETD-based site localization is no more reliable than CID. We conclude that intramolecular phosphate transfer does not affect the reliability of current or past phosphorylation data sets

Gas-Phase Rearrangements Do Not Affect Site Localization Reliability in Phosphoproteomics Data Sets

Intramolecular transfer of phosphate during collision-induced dissociation (CID) in ion-trap mass spectrometers has recently been described. Because phosphorylation events are assigned to discrete serine, threonine, and tyrosine residues based on the presence of site-determining ions in MS/MS spectra, phosphate transfer may invalidate or confound site localization in published large-scale phosphorylation data sets. Here, we present evidence for the occurrence of this phenomenon using synthetic phosphopeptide libraries, specifically for doubly charged species. We found, however, that the extent of the transfer reaction was insufficient to cause localization of phosphorylation sites to incorrect residues. We further compared CID to electron-transfer dissociation (ETD) for site localization using synthetic libraries and a large-scale yeast phosphoproteome experiment. The agreement in site localization was >99.5 and 93%, respectively, suggesting that ETD-based site localization is no more reliable than CID. We conclude that intramolecular phosphate transfer does not affect the reliability of current or past phosphorylation data sets

A High-Throughput, Multiplexed Kinase Assay Using a Benchtop Orbitrap Mass Spectrometer To Investigate the Effect of Kinase Inhibitors on Kinase Signaling Pathways

Protein phosphorylation is an important and ubiquitous post-translational modification in eukaryotic biological systems. The KAYAK (<u>K</u>inase <u>A</u>ctivit<u>Y</u> <u>A</u>ssay for <u>K</u>inome profiling) assay measures the phosphorylation rates of dozens of peptide substrates simultaneously, directly from cell lysates. Here, we simplified the assay by removing the phosphopeptide enrichment step, increasing throughput while maintaining similar data quality. We term this new method, direct-KAYAK, because kinase activities were measured directly from reaction mixtures after desalting. In addition, new peptides were included to profile additional kinase pathways and redundant substrate peptides were removed. Finally, the method is now performed in 96-well plate format using a benchtop orbitrap mass spectrometer and the Pinpoint software package for improved data analysis. We applied the new high-throughput method to measure IC₅₀ values for kinases involved in monocyte-to-macrophage differentiation, a process important for inflammation and the immune response

A Turn-Key Approach for Large-Scale Identification of Complex Posttranslational Modifications

The conjugation of complex post-translational modifications (PTMs) such as glycosylation and Small Ubiquitin-like Modification (SUMOylation) to a substrate protein can substantially change the resulting peptide fragmentation pattern compared to its unmodified counterpart, making current database search methods inappropriate for the identification of tandem mass (MS/MS) spectra from such modified peptides. Traditionally it has been difficult to develop new algorithms to identify these atypical peptides because of the lack of a large set of annotated spectra from which to learn the altered fragmentation pattern. Using SUMOylation as an example, we propose a novel approach to generate large MS/MS training data from modified peptides and derive an algorithm that learns properties of PTM-specific fragmentation from such training data. Benchmark tests on data sets of varying complexity show that our method is 80–300% more sensitive than current state-of-the-art approaches. The core concepts of our method are readily applicable to developing algorithms for the identifications of peptides with other complex PTMs

Multiplex Targeted Proteomic Assay for Biomarker Detection in Plasma: A Pancreatic Cancer Biomarker Case Study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility

Multiplex Targeted Proteomic Assay for Biomarker Detection in Plasma: A Pancreatic Cancer Biomarker Case Study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility

Multiplex Targeted Proteomic Assay for Biomarker Detection in Plasma: A Pancreatic Cancer Biomarker Case Study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility