Label-Free Quantitation and Mapping of the ErbB2 Tumor Receptor by Multiple Protease Digestion with Data-Dependent (MS1) and Data-Independent (MS2) Acquisitions

Automating Assignment, Quantitation, and Biological Annotation of Redox Proteomics Datasets with ProteoSushi

Redox proteomics plays an increasingly important role characterizing the cellular redox state and redox signaling networks. As these datasets grow larger and identify more redox regulated sites in proteins, they provide a systems-wide characterization of redox regulation across cellular organelles and regulatory networks. However, these large proteomic datasets require substantial data processing and analysis in order to fully interpret and comprehend the biological impact of oxidative posttranslational modifications. We therefore developed ProteoSushi, a software tool to biologically annotate and quantify redox proteomics and other modification-specific proteomics datasets. ProteoSushi can be applied to differentially alkylated samples to assay overall cysteine oxidation, chemically labeled samples such as those used to profile the cysteine sulfenome, or any oxidative posttranslational modification on any residue.Here we demonstrate how to use ProteoSushi to analyze a large, public cysteine redox proteomics dataset. ProteoSushi assigns each modified peptide to shared proteins and genes, sums or averages signal intensities for each modified site of interest, and annotates each modified site with the most up-to-date biological information available from UniProt. These biological annotations include known functional roles or modifications of the site, the protein domain(s) that the site resides in, the protein's subcellular location and function, and more.

ProteoSushi: A Software Tool to Biologically Annotate and Quantify Modification-Specific, Peptide-Centric Proteomics Data Sets

Large-scale proteomic profiling of protein post-translational modifications has provided important insights into the regulation of cell signaling and disease. These modification-specific proteomics workflows nearly universally enrich modified peptides prior to mass spectrometry analysis, but protein-centric proteomic software tools have many limitations evaluating and interpreting these peptide-centric data sets. We, therefore, developed ProteoSushi, a software tool tailored to analysis of each modified site in peptide-centric proteomic data sets that is compatible with any post-translational modification or chemical label. ProteoSushi uses a unique approach to assign identified peptides to shared proteins and genes, minimizing redundancy by prioritizing shared assignments based on UniProt annotation score and optional user-supplied protein/gene lists. ProteoSushi simplifies quantitation by summing or averaging intensities for each modified site, merging overlapping peptide charge states, missed cleavages, spectral matches, and variable modifications into a single value. ProteoSushi also annotates each PTM site with the most up-to-date biological information available from UniProt, such as functional roles or known modifications, the protein domain in which the site resides, the protein's subcellular location and function, and more. ProteoSushi has a graphical user interface for ease of use. ProteoSushi's flexibility and combination of analysis features streamlines peptide-centric data processing and knowledge mining of large modification-specific proteomics data sets.

Phospho-Ser784-VCP Is Required for DNA Damage Response and Is Associated with Poor Prognosis of Chemotherapy-Treated Breast Cancer

Spatiotemporal protein reorganization at DNA damage sites induced by genotoxic chemotherapies is crucial for DNA damage response (DDR), which influences treatment response by directing cancer cell fate. This process is orchestrated by valosin-containing protein (VCP), an AAA+ ATPase that extracts polyubiquinated chromatin proteins and facilitates their turnover. However, because of the essential and pleiotropic effects of VCP in global proteostasis, it remains challenging practically to understand and target its DDR-specific functions. We describe a DNA-damage-induced phosphorylation event (Ser⁷⁸⁴), which selectively enhances chromatin-associated protein degradation mediated by VCP and is required for DNA repair, signaling, and cell survival. These functional effects of Ser⁷⁸⁴ phosphorylation on DDR correlate with a decrease in VCP association with chromatin, cofactors NPL4/UFD1, and polyubiquitinated substrates. Clinically, high phospho-Ser⁷⁸⁴-VCP levels are significantly associated with poor outcome among chemotherapy-treated breast cancer patients. Thus, Ser⁷⁸⁴ phosphorylation is a DDR-specific enhancer of VCP function and a potential predictive biomarker for chemotherapy treatments.

A clickable probe for versatile characterization of S-nitrosothiols

S-nitrosation of cysteine thiols (SNOs), commonly referred to as S-nitrosylation, is a cysteine oxoform that plays an important role in cellular signaling and impacts protein function and stability. Direct labeling of SNOs in cells with the flexibility to perform a wide range of cellular and biochemical assays remains a bottleneck as all SNO-targeted probes to date employ a single analytical modality such as biotin or a specific fluorophore. We therefore developed a clickable, alkyne-containing SNO probe 'PBZyn' based on the o-phosphino-benzoyl group warhead that enables multi-modal analysis via click conjugation. We demonstrate the utility of PBZyn to assay SNOs using in situ cellular imaging, protein blotting and affinity purification, as well as mass spectrometry. The flexible PBZyn probe will greatly facilitate investigation into the regulation of SNOs.

Systems level profiling of arginine starvation reveals MYC and ERK adaptive metabolic reprogramming

Arginine auxotrophy due to the silencing of argininosuccinate synthetase 1 (ASS1) occurs in many carcinomas and in the majority of sarcomas. Arginine deiminase (ADI-PEG20) therapy exploits this metabolic vulnerability by depleting extracellular arginine, causing arginine starvation. ASS1-negative cells develop resistance to ADI-PEG20 through a metabolic adaptation that includes re-expressing ASS1. As arginine-based multiagent therapies are being developed, further characterization of the changes induced by arginine starvation is needed. In order to develop a systems-level understanding of these changes, activity-based proteomic profiling (ABPP) and phosphoproteomic profiling were performed before and after ADI-PEG20 treatment in ADI-PEG20-sensitive and resistant sarcoma cells. When integrated with metabolomic profiling, this multi-omic analysis reveals that cellular response to arginine starvation is mediated by adaptive ERK signaling and activation of the Myc–Max transcriptional network. Concomitantly, these data elucidate proteomic changes that facilitate oxaloacetate production by enhancing glutamine and pyruvate anaplerosis and altering lipid metabolism to recycle citrate for oxidative glutaminolysis. Based on the complexity of metabolic and cellular signaling interactions, these multi-omic approaches could provide valuable tools for evaluating response to metabolically targeted therapies.

Redox Systems Biology: Harnessing the Sentinels of the Cysteine Redoxome

Significance: Cellular redox processes are highly interconnected, yet not in equilibrium, and governed by a wide range of biochemical parameters. Technological advances continue refining how specific redox processes are regulated, but broad understanding of the dynamic interconnectivity between cellular redox modules remains limited. Systems biology investigates multiple components in complex environments and can provide integrative insights into the multifaceted cellular redox state. This review describes the state of the art in redox systems biology as well as provides an updated perspective and practical guide for harnessing thousands of cysteine sensors in the redoxome for multiparameter characterization of cellular redox networks. Recent Advances: Redox systems biology has been applied to genome-scale models and large public datasets, challenged common conceptions, and provided new insights that complement reductionist approaches. Advances in public knowledge and user-friendly tools for proteome-wide annotation of cysteine sentinels can now leverage cysteine redox proteomics datasets to provide spatial, functional, and protein structural information. Critical Issues: Careful consideration of available analytical approaches is needed to broadly characterize the systems-level properties of redox signaling networks and be experimentally feasible. The cysteine redoxome is an informative focal point since it integrates many aspects of redox biology. The mechanisms and redox modules governing cysteine redox regulation, cysteine oxidation assays, proteome-wide annotation of the biophysical and biochemical properties of individual cysteines, and their clinical application are discussed. Future Directions: Investigating the cysteine redoxome at a systems level will uncover new insights into the mechanisms of selectivity and context dependence of redox signaling networks.

Multiplex and Label-Free Relative Quantification Approach for Studying Protein Abundance of Drug Metabolizing Enzymes in Human Liver Microsomes Using SWATH-MS

We describe a sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) based method for label-free, simultaneous, relative quantification of drug metabolism enzymes in human liver microsomes (HLM; n = 78). In-solution tryptic digestion was aided by a pressure cycling method, which allowed a 90 min incubation time, a significant reduction over classical protocols (12-18 h). Digested peptides were separated on an Acquity UHPLC Peptide BEH C18 column using a 60 min gradient method at a flow rate of 0.100 mL/min. The quadrupole-time-of-flight mass spectrometer (ESI-QTOFMS) was operated in positive electrospray ionization mode, and data were acquired by data-dependent acquisition (DDA) and SWATH-MS^ALL mode. A pooled HLM sample was used as a quality control to evaluate variability in digestion and quantification among different batches, and inter-batch %CV for various proteins was between 3.1 and 7.8%. Spectral library generated from the DDA data identified 1855 distinct proteins and 25 681 distinct peptides at a 1% global false discovery rate (FDR). SWATH data were queried and analyzed for 10 major cytochrome P450 (CYP) enzymes using Skyline, a targeted data extraction software. Further, correlation analysis was performed between functional activity, protein, and mRNA expression for ten CYP enzymes. Pearson correlation coefficient (r) between protein and activity for CYPs ranged from 0.314 (CYP2C19) to 0.767 (CYP2A6). A strong correlation was found between CYP3A4 and CYP3A5 abundance and activity determined using midazolam and testosterone (r > 0.600, p < 0.001). Protein-to-activity correlation was moderate (r > 0.400-0.600, p < 0.001) for CYP1A2, CYP2A6, CYP2B6, CYP2C9, and CYP2E1 and significant but poor (r < 0.400, p < 0.05) for CYP2C8, CYP2C19, and CYP2D6. The findings suggest the suitability of SWATH-MS based method as a valuable and relatively fast analytical technique for relative quantification of proteins in complex biological samples. We also show that protein abundance is a better surrogate than mRNA to predict the activity of CYP activity.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

How may targeted proteomics complement genomic data in breast cancer?

INTRODUCTION

Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.

Multiplexed, Scheduled, High-Resolution Parallel Reaction Monitoring on a Full Scan QqTOF Instrument with Integrated Data-Dependent and Targeted Mass Spectrometric Workflows

Recent advances in commercial mass spectrometers with higher resolving power and faster scanning capabilities have expanded their functionality beyond traditional data-dependent acquisition (DDA) to targeted proteomics with higher precision and multiplexing. Using an orthogonal quadrupole time-of flight (QqTOF) LC-MS system, we investigated the feasibility of implementing large-scale targeted quantitative assays using scheduled, high resolution multiple reaction monitoring (sMRM-HR), also referred to as parallel reaction monitoring (sPRM). We assessed the selectivity and reproducibility of PRM, also referred to as parallel reaction monitoring, by measuring standard peptide concentration curves and system suitability assays. By evaluating up to 500 peptides in a single assay, the robustness and accuracy of PRM assays were compared to traditional SRM workflows on triple quadrupole instruments. The high resolution and high mass accuracy of the full scan MS/MS spectra resulted in sufficient selectivity to monitor 6-10 MS/MS fragment ions per target precursor, providing flexibility in postacquisition assay refinement and optimization. The general applicability of the sPRM workflow was assessed in complex biological samples by first targeting 532 peptide precursor ions in a yeast lysate, and then 466 peptide precursors from a previously generated candidate list of differentially expressed proteins in whole cell lysates from E. coli. Lastly, we found that sPRM assays could be rapidly and efficiently developed in Skyline from DDA libraries when acquired on the same QqTOF platform, greatly facilitating their successful implementation. These results establish a robust sPRM workflow on a QqTOF platform to rapidly transition from discovery analysis to highly multiplexed, targeted peptide quantitation.

Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications

In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late.

The role of protein and peptide separation before mass spectrometry analysis in clinical proteomics

The purpose of clinical proteomics is to characterise protein profiles of a plethora of diseases with the aim of finding specific biomarkers. These are particularly valuable for early diagnosis, and represent key molecules suitable to elucidate pathogenic mechanisms. Samples deriving from patients (i.e. blood, urine, cerebrospinal fluid, biopsies) are the sources for clinical proteomics. Due to the complexity of the extracted samples their direct analysis is unachievable. Any analytical clinical proteomics study should start with the choice of the optimal combination of strategies with respect to both sample preparations and MS approaches. Protein or peptide fractionation (off-line or on-line) is essential to reduce complexity of biological samples and to achieve the most complete and reproducible analysis. The aim of this review is to introduce the readers to a functional range of strategies to help scientists in their proteomics set up. In particular, the separation approaches of proteins or peptides (both gel-based and gel-free) are reviewed with special attention paid to their advantages and limitations, and to the different liquid chromatography techniques used to peptide fractionation after protein enzymatic digestion and before their detection. Finally, the role of mass spectrometry (MS) for protein identification and quantification is discussed including emerging MS data acquisition strategies.

Variation and quantification among a target set of phosphopeptides in human plasma by multiple reaction monitoring and SWATH-MS2 data-independent acquisition

Human plasma contains proteins that reflect overall health and represents a rich source of proteins for identifying and understanding disease pathophysiology. However, few studies have investigated changes in plasma phosphoproteins. In addition, little is known about the normal variations in these phosphoproteins, especially with respect to specific sites of modification. To address these questions, we evaluated variability in plasma protein phosphorylation in healthy individuals using multiple reaction monitoring (MRM) and SWATH-MS2 data-independent acquisition. First, we developed a discovery workflow for phosphopeptide enrichment from plasma and identified targets for MRM assays. Next, we analyzed plasma from healthy donors using an analytical workflow consisting of MRM and SWATH-MS2 that targeted phosphopeptides from 58 and 68 phosphoproteins, respectively. These two methods produced similar results showing low variability in 13 phosphosites from 10 phosphoproteins (CVinter < 30%) and high interpersonal variation of 16 phosphosites from 14 phosphoproteins (CVinter > 30%). Moreover, these phosphopeptides originate from phosphoproteins involved in cellular processes governing homeostasis, immune response, cell-extracellular matrix interactions, lipid and sugar metabolism, and cell signaling. This limited assessment of technical and biological variability in phosphopeptides generated from plasma phosphoproteins among healthy volunteers constitutes a reference for future studies that target protein phosphorylation as biomarkers.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Multiple enzymatic digestions and ion mobility separation improve quantification of bacterial ribosomal proteins by data independent acquisition liquid chromatography-mass spectrometry

Mass spectrometry-based quantification of ribosomal proteins (r-proteins) associated with mature ribosomes and ribosome assembly complexes is typically accomplished by relative quantification strategies. These strategies provide information on the relative stoichiometry of proteins within the complex compared to a wild-type strain. Here we have evaluated the applicability of a label-free approach, enhanced liquid chromatography–mass spectrometry (LC–MS^E), for absolute “ribosome-centric” quantification of r-proteins in Escherichia coli mature ribosomes. Because the information obtained in this experiment is related to the number of peptides identified per protein, experimental conditions that allow accurate and reproducible quantification of r-proteins were found. Using an additional dimension of gas-phase separation through ion mobility and the use of multiple endoproteinase digestion significantly improved quantification of proteins associated with mature ribosomes. The actively translating ribosomes (polysomes) contain amounts of proteins consistent with their known stoichiometry within the complex. These measurements exhibited technical and biological reproducibilities at %CV less than 15% and 35%, respectively. The improved LC–MS^E approach described here can be used to characterize in vivo ribosome assembly complexes captured during ribosome biogenesis and assembly under different perturbations (e.g., antibiotics, deletion mutants of assembly factors, oxidative stress, nutrient deprivation). Quantitative analysis of these captured complexes will provide information relating to the interplay and dynamics of how these perturbations interfere with the assembly process.