Synthetic peptide arrays for pathway-level protein monitoring by liquid chromatography-tandem mass spectrometry

Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling

In spite of extensive studies of cellular signaling, many fundamental processes such as pathway integration, cross-talk, and feedback remain poorly understood. To enable integrated and quantitative measurements of cellular biochemical activities, we have developed the Quantitative Cell Proteomics Atlas (QCPA). QCPA consists of panels of targeted mass spectrometry assays to determine the abundance and stoichiometry of regulatory post-translational modifications of sentinel proteins from most known physiologic and pathogenic signaling pathways in human cells. QCPA currently profiles 1 913 peptides from 469 effectors of cell surface signaling, apoptosis, stress response, gene expression, quiescence, and proliferation. For each protein, QCPA includes triplets of isotopically labeled peptides covering known post-translational regulatory sites to determine their stoichiometries and unmodified protein regions to measure total protein abundance. The QCPA framework incorporates analytes to control for technical variability of sample preparation and mass spectrometric analysis, including TrypQuant, a synthetic substrate for accurate quantification of proteolysis efficiency for proteins containing chemically modified residues. The ability to precisely and accurately quantify most known signaling pathways should enable improved chemoproteomic approaches for the comprehensive analysis of cell signaling and clinical proteomics of diagnostic specimens. QCPA is openly available at https://qcpa.mskcc.org.

Optimization by infusion of multiple reaction monitoring transitions for sensitive quantification of peptides by liquid chromatography/mass spectrometry

RATIONALE

In peptide quantification by liquid chromatography/mass spectrometry (LC/MS), the optimization of multiple reaction monitoring (MRM) parameters is essential for sensitive detection. We have compared different approaches to build MRM assays, based either on flow injection analysis (FIA) of isotopically labelled peptides, or on the knowledge and the prediction of the best settings for MRM transitions and collision energies (CE). In this context, we introduce MRMOptimizer, an open-source software tool that processes spectra and assists the user in selecting transitions in the FIA workflow.

METHODS

MS/MS spectral libraries with CE voltages from 10 to 70 V are automatically acquired in FIA mode for isotopically labelled peptides. Then MRMOptimizer determines the optimal MRM settings for each peptide. To assess the quantitative performance of our approach, 155 peptides, representing 84 proteins, were analysed by LC/MRM-MS and the peak areas were compared between: (A) the MRMOptimizer-based workflow, (B1) the SRMAtlas transitions set used 'as-is'; (B2) the same SRMAtlas set with CE parameters optimized by Skyline.

RESULTS

51% of the three most intense transitions per peptide were shown to be common to both A and B1/B2 methods, and displayed similar sensitivity and peak area distributions. The peak areas obtained with MRMOptimizer for transitions sharing either the precursor ion charge state or the fragment ions with the SRMAtlas set at unique transitions were increased 1.8- to 2.3-fold. The gain in sensitivity using MRMOptimizer for transitions with different precursor ion charge state and fragment ions (8% of the total), reaches a ~ 11-fold increase.

CONCLUSIONS

Isotopically labelled peptides can be used to optimize MRM transitions more efficiently in FIA than by searching databases. The MRMOptimizer software is MS independent and enables the post-acquisition selection of MRM parameters. Coefficients of variation for optimal CE values are lower than those obtained with the SRMAtlas approach (B2) and one additional peptide was detected. Copyright © 2017 John Wiley & Sons, Ltd.

Cand1 promotes assembly of new SCF complexes through dynamic exchange of F box proteins

The modular SCF (Skp1, cullin, and F box) ubiquitin ligases feature a large family of F box protein substrate receptors that enable recognition of diverse targets. However, how the repertoire of SCF complexes is sustained remains unclear. Real-time measurements of formation and disassembly indicate that SCF(Fbxw7) is extraordinarily stable, but, in the Nedd8-deconjugated state, the cullin-binding protein Cand1 augments its dissociation by one-million-fold. Binding and ubiquitylation assays show that Cand1 is a protein exchange factor that accelerates the rate at which Cul1-Rbx1 equilibrates with multiple F box protein-Skp1 modules. Depletion of Cand1 from cells impedes recruitment of new F box proteins to pre-existing Cul1 and profoundly alters the cellular landscape of SCF complexes. We suggest that catalyzed protein exchange may be a general feature of dynamic macromolecular machines and propose a hypothesis for how substrates, Nedd8, and Cand1 collaborate to regulate the cellular repertoire of SCF complexes.

Targeted protein identification, quantification and reporting for high-resolution nanoflow targeted peptide monitoring

Mass spectrometry-based targeted proteomic assays are experiencing a surge in awareness due to the diverse possibilities arising from the re-application of traditional LC-SRM technology. The FDA-approved quantitative LC-SRM-pipeline in drug discovery motivates the use to quantitatively validate putative proteomic biomarkers. However, complexity of biological specimens bears a huge challenge to identify, in parallel, specific peptides and proteins of interest from large biomarker candidate lists. Methods have been devised to increase scan speeds, improve detection specificity and verify quantitative SRM-features. In contrast, high-resolution mass spectrometers could be used to improve reliability and precision of targeted proteomics assays. Here, we present a new method for identifying, quantifying and reporting peptides in high-resolution targeted proteomics experiments performed on an orbitrap hybrid instrument using stable isotope-labeled internal reference peptides. This high precision targeted peptide monitoring (TPM) method has unique advantages over existing techniques, including the need to only detect the most abundant product ion of a given target for confident peptide identification using a scoring function that evaluates assay performance based on 1) m/z-mass accuracy, 2) retention time accuracy of observed species relative to prediction, and 3) retention time accuracy relative to internal reference peptides. Further, we show management of multiplexed precision TPM-assays using sentinel peptide standards. This article is part of a Special Issue entitled: From protein structures to clinical applications.

A systematic model of the LC-MS proteomics pipeline

Motivation

Mass spectrometry is a complex technique used for large-scale protein profiling with clinical and pharmaceutical applications. While individual components in the system have been studied extensively, little work has been done to integrate various modules and evaluate them from a systems point of view.

Results

In this work, we investigate this problem by putting together the different modules in a typical proteomics work flow, in order to capture and analyze key factors that impact the number of identified peptides and quantified proteins, protein quantification error, differential expression results, and classification performance. The proposed proteomics pipeline model can be used to optimize the work flow as well as to pinpoint critical bottlenecks worth investing time and resources into for improving performance. Using the model-based approach proposed here, one can study systematically the critical problem of proteomic biomarker discovery, by means of simulation using ground-truthed synthetic MS data.

Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that is emerging in the field of proteomics as a complement to untargeted shotgun methods. SRM is particularly useful when predetermined sets of proteins, such as those constituting cellular networks or sets of candidate biomarkers, need to be measured across multiple samples in a consistent, reproducible and quantitatively precise manner. Here we describe how SRM is applied in proteomics, review recent advances, present selected applications and provide a perspective on the future of this powerful technology.

Applying selected reaction monitoring to targeted proteomics

Selected reaction monitoring (SRM) is a highly selective and sensitive mass spectrometric methodology for precise and accurate quantification of low-abundant proteins in complex mixtures and for characterization of modified peptides, and constitutes the method of choice in targeted proteomics. Owing to its outstanding features, SRM arises as an alternative to antibody-based assays for discovery and validation of clinically relevant biomarkers, a topic that is tackled in this article. Several of the obstacles encountered in SRM experiments, mainly those derived from shared physicochemical properties of peptides (e.g., mass, charge and chromatographic retention time), can compromise selectivity and quantitation. We illustrate how to circumvent these limitations on the basis of using time-scheduled chromatographic approaches and choosing appropriate spectrometric conditions, including the careful selection of the precursor and diagnostic ions.

Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery

Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.