Single-step enrichment by Ti4+-IMAC and label-free quantitation enables in-depth monitoring of phosphorylation dynamics with high reproducibility and temporal resolution

Integrative phosphoproteomic analyses reveal hemostatic-endothelial signaling interplay

BACKGROUND

The vascular endothelial cell (EC) monolayer plays a crucial part in maintaining hemostasis. An extensive array of G protein-coupled receptors allows ECs to dynamically act on key hemostatic stimuli such as thrombin and histamine. The impact of these individual stimuli on EC signal transduction has been the subject of various studies, but insight into discordant and concordant EC signaling between different G protein-coupled receptors remains limited.

OBJECTIVES

To elucidate histamine and protease-activated receptor (PAR1-4) signaling cascades in ECs, discern overlapping and diverging regulation between these stimuli and their effect on the EC monolayer.

METHODS

We employed stable isotope labeling by amino acids in cell culture mass spectrometry-based phosphoproteomics on in vitro cultured blood outgrowth ECs stimulated with histamine and different PAR1 to 4 peptides. We investigated key phosphosites through immuno(fluorescence) staining and determined effects on barrier function through transendothelial resistance assays.

RESULTS

EC histamine activation initiated an extensive (kinase) signaling network (including MAPK3, STAT3, and CTNND1). PAR1 and PAR2 receptors induced highly similar signaling cascades, whereas PAR3 and PAR4 induced minimal phospho-regulation. Integration of all applied stimuli indicated uniquely activated proteins between both stimuli, as well as a general overlapping activation of cell junction and actin cytoskeletal proteins.

CONCLUSION

We provide an integrative phosphoproteomic analysis of histamine and PAR agonists in the endothelium that highlights the endothelial response programs that are at the basis of regulating hemostasis.

Label-Free Quantitative Phosphoproteomics in the Fission Yeast Schizosaccharomyces pombe

Protein phosphorylation is a dynamic, reversible posttranslational modification that plays an important role in the regulation of cell signaling. Recently, label-free quantitative (LFQ) phosphoproteomics has become a powerful tool to analyze the phosphorylation of proteins within complex samples. In this chapter, we describe how to apply LFQ phosphoproteomics that is based on Fe-IMAC phosphopeptide enrichment followed by strong anion exchange (SAX) and porous graphitic carbon (PGC) fractionation strategies for identification and quantification of changes in the phosphoproteome in the fission yeast Schizosaccharomyces pombe.

Proteomic and network pharmacology analyses reveal S100A8 as the anti-inflammatory target of Yunpi Jiedu Tongluo Qushi Granule in the treatment of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovial inflammation. RA has a global prevalence between 0.5 % and 1 % although its pathogenesis is not completely understood. Chinese herbal medicine such as Yunpi Jiedu Tongluo Qushi Granule (YJTQG) is one of the treatments for RA. However, the underlying mechanism of action is unclear. Here, analysis of clinical samples reveals that YJTQG can reduce the inflammatory factors and alleviate the symptoms of RA patients. Quantitative proteomic analysis of serum proteomes of RA patients identifies the potential therapeutic targets of YJTQG. We use biochemical experiments to validate several differentially expressed proteins, discover S100A8 as a possible therapeutic target of YJTQG, and analyze the correlation between S100A8 and several known RA biomarkers. Network pharmacology analysis discloses COX1/2 and NOS2 as potential targets of key compounds in YJTQG and protein-protein interaction network analysis reveals TNFα, IL-6, and STAT3 as possible core targets of YJTQG. Bioinformatic and patient sample analyses indicate that YJTQG may reduce S100A8 expression by suppressing its transcription. Mechanistically, we find that kaempferol and quercetin in YJTQG may reduce the expression of S100A8 by inhibiting the phosphorylation, nuclear translocation, and transcriptional activity of p65 in the lipopolysaccharide-stimulated RAW264.7 cells. Therefore, our work demonstrates that S100A8 is a potential therapeutic target of YJTQG for RA, which may provide a new direction for developing new treatments for RA patients.

In-Depth Endogenous Phosphopeptidomics of Serum with Zirconium(IV)-Grafted Mesoporous Silica Enrichment

Detection of endogenous peptides, especially those with modifications (such as phosphorylation) in biofluids, can serve as an indicator of intracellular pathophysiology. Although great progress has been made in phosphoproteomics in recent years, endogenous phosphopeptidomics has largely lagged behind. One main hurdle in endogenous phosphopeptidomics analysis is the coexistence of proteins and highly abundant nonmodified peptides in complex matrices. In this study, we developed an approach using zirconium(IV)-grafted mesoporous beads to enrich phosphopeptides, followed by analysis with a high resolution nanoRPLC-MS/MS system. The bifunctional material was first tested with digests of standard phosphoproteins and HeLa cell lysates, with excellent enrichment performance achieved. Given the size exclusion nature, the beads were directly applied for endogenous phosphopeptidomic analysis of serum samples from pancreatic ductal adenocarcinoma (PDAC) patients and controls. In total, 329 endogenous phosphopeptides (containing 113 high confidence sites) were identified across samples, by far the largest endogenous phosphopeptide data set cataloged to date. In addition, the method was readily applied for phosphoproteomics of the same set of samples, with 172 phosphopeptides identified and significant changes in dozens of phosphopeptides observed. Given the simplicity and robustness of the proposed method, we envision that it can be readily used for comprehensive phosphorylation studies of serum and other biofluid samples.

Endothelium-mediated regulation of platelet activation: Involvement of multiple protein kinases

The endothelial regulation of platelet activity is incompletely understood. Here we describe novel approaches to find molecular pathways implicated on the platelet-endothelium interaction. Using high-shear whole-blood microfluidics, employing coagulant or non-coagulant conditions at physiological temperature, we observed that the presence of human umbilical vein endothelial cells (HUVEC) strongly suppressed platelet adhesion and activation, via the collagen receptor glycoprotein VI (GPVI) and the PAR receptors for thrombin. Real-time monitoring of the cytosolic Ca2+ rises in the platelets indicated no major improvement of inhibition by prostacyclin or nitric oxide. Similarly under stasis, exposure of isolated platelets to HUVEC reduced the Ca2+ responses by collagen-related peptide (CRP-XL, GPVI agonist) and thrombin (PAR agonist). We then analyzed the label-free phosphoproteome of platelets (three donors), exposed to HUVEC, CRP-XL, and/or thrombin. High-resolution mass spectrometry gave 5463 phosphopeptides, corresponding to 1472 proteins, with good correlation between biological and technical replicates (R > .86). Stringent filtering steps revealed 26 regulatory pathways (Reactome) and 143 regulated kinase substrates (PhosphoSitePlus), giving a set of protein phosphorylation sites that was differentially (44) or similarly (110) regulated by HUVEC or agonist exposure. The differential regulation was confirmed by stable-isotope analysis of platelets from two additional donors. Substrate analysis indicated major roles of poorly studied protein kinase classes (MAPK, CDK, DYRK, STK, PKC members). Collectively, these results reveal a resetting of the protein phosphorylation profile in platelets exposed to endothelium or to conventional agonists and to endothelium-promoted activity of a multi-kinase network, beyond classical prostacyclin and nitric oxide actors, that may contribute to platelet inhibition.

Protein degradation by human 20S proteasomes elucidates the interplay between peptide hydrolysis and splicing

If and how proteasomes catalyze not only peptide hydrolysis but also peptide splicing is an open question that has divided the scientific community. The debate has so far been based on immunopeptidomics, in vitro digestions of synthetic polypeptides as well as ex vivo and in vivo experiments, which could only indirectly describe proteasome-catalyzed peptide splicing of full-length proteins. Here we develop a workflow-and cognate software - to analyze proteasome-generated non-spliced and spliced peptides produced from entire proteins and apply it to in vitro digestions of 15 proteins, including well-known intrinsically disordered proteins such as human tau and α-Synuclein. The results confirm that 20S proteasomes produce a sizeable variety of cis-spliced peptides, whereas trans-spliced peptides are a minority. Both peptide hydrolysis and splicing produce peptides with well-defined characteristics, which hint toward an intricate regulation of both catalytic activities. At protein level, both non-spliced and spliced peptides are not randomly localized within protein sequences, but rather concentrated in hotspots of peptide products, in part driven by protein sequence motifs and proteasomal preferences. At sequence level, the different peptide sequence preference of peptide hydrolysis and peptide splicing suggests a competition between the two catalytic activities of 20S proteasomes during protein degradation.

Using the Proteomics Toolbox to Resolve Topology and Dynamics of Compartmentalized cAMP Signaling

cAMP is a second messenger that regulates a myriad of cellular functions in response to multiple extracellular stimuli. New developments in the field have provided exciting insights into how cAMP utilizes compartmentalization to ensure specificity when the message conveyed to the cell by an extracellular stimulus is translated into the appropriate functional outcome. cAMP compartmentalization relies on the formation of local signaling domains where the subset of cAMP signaling effectors, regulators and targets involved in a specific cellular response cluster together. These domains are dynamic in nature and underpin the exacting spatiotemporal regulation of cAMP signaling. In this review, we focus on how the proteomics toolbox can be utilized to identify the molecular components of these domains and to define the dynamic cellular cAMP signaling landscape. From a therapeutic perspective, compiling data on compartmentalized cAMP signaling in physiological and pathological conditions will help define the signaling events underlying disease and may reveal domain-specific targets for the development of precision medicine interventions.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.

Phosphoproteomic analysis of FAC overload-triggered human hepatic cells reveals G2/M phase arrest

Hepatic iron overload is a universal phenomenon in patients with myelodysplastic syndromes (MDS) who undergo bone marrow transplantation and may experience the toxicity of peri- and post-bone marrow transplantation. To clarify the mechanisms of iron overload-triggered liver injury, we determined the effects of iron overload on changes in protein phosphorylation in human hepatocyte cell line HH4 in vitro by using a phosphoproteomics approach. The hepatocytes were exposed to high concentrations of ferric ammonium citrate (FAC) to build up an iron overload model in vitro. Changes in protein phosphorylation initiated by iron overloading were studied by 2D-LC/MS. We identified 335 differentially expressed phosphorylated proteins under the condition of excess hepatocyte iron, 11% of which were related to cell cycle progression. The results of phosphoproteomics showed that iron overload induced 10.9 times increase in Thr 14/Tyr 15-phosphorylated Cdk1 in HH4 cells. Flow cytometry analysis revealed that FAC-treated HH4 cells showed significant G2/M phase arrest. Our subsequent RT-PCR and Western blot experiments indicated that FAC-induced G2/M phase arrest was related to the activation of p53-p21-Cdk1, p53-14-3-3 sigma-Cdk1, and 14-3-3 gamma pathway. Our findings demonstrate the first evidence that iron overload causes G2/M arrest in HH4 hepatocytes.

Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data

Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

NTRK1/TrkA Signaling in Neuroblastoma Cells Induces Nuclear Reorganization and Intra-Nuclear Aggregation of Lamin A/C

Simple Summary

Neuroblastoma (NB) accounts for 15% of all cancer-related deaths of children. While the amplification of the Myc-N proto-oncogene (MYCN) is a major driver of aggressive NB, the expression of the neurotrophin receptor, NTRK1/TrkA, has been shown to be associated with an excellent outcome. MYCN downregulates NTRK1 expression, but it is unknown if the molecular effects of NTRK1 signaling also affect MYCN-induced networks. The aim of this study was to decipher NTRK1 signaling using an unbiased proteome and phosphoproteome approach. To this end, we realized inducible ectopic NTRK1 expression in a NB cell line with MYCN amplification and analyzed the proteomic changes upon NTRK1 activation in a time-dependent manner. In line with the phenotypes observed, NTRK1 activation induced markers of neuronal differentiation and cell cycle arrest. Most prominently, NTRK1 upregulated the expression and phosphorylation of the nuclear lamina component Lamin A/C. Moreover, NTRK1 signaling also induced the aggregation of LMNA within nucleic foci, which accompanies differentiation in other cell types.

Abstract

(1) Background: Neuroblastomas (NBs) are the most common extracranial solid tumors of children. The amplification of the Myc-N proto-oncogene (MYCN) is a major driver of NB aggressiveness, while high expression of the neurotrophin receptor NTRK1/TrkA is associated with mild disease courses. The molecular effects of NTRK1 signaling in MYCN-amplified NB, however, are still poorly understood and require elucidation. (2) Methods: Inducible NTRK1 expression was realized in four NB cell lines with (IMR5, NGP) or without MYCN amplification (SKNAS, SH-SY5Y). Proteome and phosphoproteome dynamics upon NTRK1 activation by its ligand, NGF, were analyzed in a time-dependent manner in IMR5 cells. Target validation by immunofluorescence staining and automated image processing was performed using the three other NB cell lines. (3) Results: In total, 230 proteins and 134 single phosphorylated class I phosphosites were found to be significantly regulated upon NTRK1 activation. Among known NTRK1 targets, Stathmin and the neurosecretory protein VGF were recovered. Additionally, we observed the upregulation and phosphorylation of Lamin A/C (LMNA) that accumulated inside nuclear foci. (4) Conclusions: We provide a comprehensive picture of NTRK1-induced proteome and phosphoproteome dynamics. The phosphorylation of LMNA within nucleic aggregates was identified as a prominent feature of NTRK1 signaling independent of the MYCN status of NB cells.

Systems approach reveals distinct and shared signaling networks of the four PGE2 receptors in T cells

[Figure: see text].

A data-independent acquisition-based global phosphoproteomics system enables deep profiling

Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (<0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.

Axelrod Symposium 2019: Phosphoproteomic Analysis of G-Protein-Coupled Pathways

By limiting unrestricted activation of intracellular effectors, compartmentalized signaling of cyclic nucleotides confers specificity to extracellular stimuli and is critical for the development and health of cells and organisms. Dissecting the molecular mechanisms that allow local control of cyclic nucleotide signaling is essential for our understanding of physiology and pathophysiology, but mapping the dynamics and regulation of compartmentalized signaling is a challenge. In this minireview we summarize advanced imaging and proteomics techniques that have been successfully used to probe compartmentalized cAMP signaling in eukaryotic cells. Subcellularly targeted fluorescence resonance energy transfer sensors can precisely locate and measure compartmentalized cAMP, and this allows us to estimate the range of effector activation. Because cAMP effector proteins often cluster together with their targets and cAMP regulatory proteins to form discrete cAMP signalosomes, proteomics and phosphoproteomics analysis have more recently been used to identify additional players in the cAMP-signaling cascade. We propose that the synergistic use of the techniques discussed could prove fruitful in generating a detailed map of cAMP signalosomes and reveal new details of compartmentalized signaling. Compiling a dynamic map of cAMP nanodomains in defined cell types would establish a blueprint for better understanding the alteration of signaling compartments associated with disease and would provide a molecular basis for targeted therapeutic strategies. SIGNIFICANCE STATEMENT: cAMP signaling is compartmentalized. Some functionally important cellular signaling compartments operate on a nanometer scale, and their integrity is essential to maintain cellular function and appropriate responses to extracellular stimuli. Compartmentalized signaling provides an opportunity for precision medicine interventions. Our detailed understanding of the composition, function, and regulation of cAMP-signaling nanodomains in health and disease is essential and will benefit from harnessing the right combination of advanced biochemical and imaging techniques.

Phosphoproteomics-Based Characterization of Prostaglandin E2 Signaling in T Cells

Prostaglandin E2 (PGE2) is a key lipid mediator in health and disease and serves as a crucial link between the immune response and cancer. With the advent of cancer therapies targeting PGE2 signaling pathways at different levels, there has been increased interest in mapping and understanding the complex and interconnected signaling pathways arising from the four distinct PGE2 receptors. Here, we review phosphoproteomics studies that have investigated different aspects of PGE2 signaling in T cells. These studies have elucidated PGE2's regulatory effect on T cell receptor signaling and T cell function, the key role of protein kinase A in many PGE2 signaling pathways, the temporal regulation of PGE2 signaling, differences in PGE2 signaling between different T cell subtypes, and finally, the crosstalk between PGE2 signaling pathways elicited by the four distinct PGE2 receptors present in T cells. SIGNIFICANCE STATEMENT: Through the reviewed studies, we now have a much better understanding of PGE2's signaling mechanisms and functional roles in T cells, as well as a solid platform for targeted and functional studies of specific PGE2-triggered pathways in T cells.

Global Phosphoproteome Analysis Using High-Field Asymmetric Waveform Ion Mobility Spectrometry on a Hybrid Orbitrap Mass Spectrometer

Mass spectrometry is the premier tool for identifying and quantifying protein phosphorylation on a global scale. Analysis of phosphopeptides requires enrichment, and even after the samples remain highly complex and exhibit broad dynamic range of abundance. Achieving maximal depth of coverage for phosphoproteomics therefore typically necessitates offline liquid chromatography prefractionation, a time-consuming and laborious approach. Here, we incorporate a recently commercialized aerodynamic high-field asymmetric waveform ion mobility spectrometry (FAIMS) device into the phosphoproteomic workflow. We characterize the effects of phosphorylation on the FAIMS separation, describe optimized compensation voltage settings for unlabeled phosphopeptides, and demonstrate the advantages of FAIMS-enabled gas-phase fractionation. Standard FAIMS single-shot analyses identified around 15-20% additional phosphorylation sites than control experiments without FAIMS. In comparison to liquid chromatography prefractionation, FAIMS experiments yielded similar or superior results when analyzing up to four discrete gas-phase fractions. Although using FAIMS led to a modest reduction in the precision of quantitative measurements when using label-free approaches, the data collected with FAIMS yielded a 26% increase in total reproducible measurements. Overall, we conclude that the new FAIMS technology is a valuable addition to any phosphoproteomic workflow, with greater benefits emerging from longer analyses and higher amounts of material.

Zirconium(IV)-IMAC Revisited: Improved Performance and Phosphoproteome Coverage by Magnetic Microparticles for Phosphopeptide Affinity Enrichment

Phosphopeptide enrichment is an essential step in large-scale, quantitative phosphoproteomics by mass spectrometry. Several phosphopeptide affinity enrichment techniques exist, such as immobilized metal-ion affinity chromatography (IMAC) and metal oxide affinity chromatography (MOAC). We compared zirconium(IV) IMAC (Zr-IMAC) magnetic microparticles to more commonly used titanium(IV) IMAC (Ti-IMAC) and TiO₂ magnetic microparticles for phosphopeptide enrichment from simple and complex protein samples prior to phosphopeptide sequencing and characterization by mass spectrometry (liquid chromatography-tandem mass spectrometry, LC-MS/MS). We optimized sample-loading conditions to increase phosphopeptide recovery for Zr-IMAC-, Ti-IMAC-, and TiO₂-based workflows by 22, 24, and 35%, respectively. The optimized protocol resulted in improved performance of Zr-IMAC over Ti-IMAC and TiO₂ as well as high-performance liquid chromatography-based Fe(III)-IMAC with up to 23% more identified phosphopeptides. The different enrichment chemistries showed a high degree of overlap but also differences in phosphopeptide selectivity and complementarity. We conclude that Zr-IMAC improves phosphoproteome coverage and recommend that this complementary and scalable affinity enrichment method is more widely used in biological and biomedical studies of cell signaling and the search for biomarkers. Data are available via ProteomeXchange with identifier PXD018273.

Low-Dose Sorafenib Acts as a Mitochondrial Uncoupler and Ameliorates Nonalcoholic Steatohepatitis

Nonalcoholic steatohepatitis (NASH) is becoming one of the leading causes of hepatocellular carcinoma (HCC). Sorafenib is the only first-line therapy for advanced HCC despite its serious adverse effects. Here, we report that at an equivalent of approximately one-tenth the clinical dose for HCC, sorafenib treatment effectively prevents the progression of NASH in both mice and monkeys without any observed significant adverse events. Mechanistically, sorafenib's benefit in NASH is independent of its canonical kinase targets in HCC, but involves the induction of mild mitochondrial uncoupling and subsequent activation of AMP-activated protein kinase (AMPK). Collectively, our findings demonstrate a previously unappreciated therapeutic effect and signaling mechanism of low-dose sorafenib treatment in NASH. We envision that this new therapeutic strategy for NASH has the potential to translate into a beneficial anti-NASH therapy with fewer adverse events than is observed in the drug's current use in HCC.

The proteome and its dynamics: A missing piece for integrative multi-omics in schizophrenia

The complex and heterogeneous pathophysiology of schizophrenia can be deconstructed by integration of large-scale datasets encompassing genes through behavioral phenotypes. Genome-wide datasets are now available for genetic, epigenetic and transcriptomic variations in schizophrenia, which are then analyzed by newly devised systems biology algorithms. A missing piece, however, is the inclusion of information on the proteome and its dynamics in schizophrenia. Proteomics has lagged behind omics of the genome, transcriptome and epigenome since analytic platforms were relatively less robust for proteins. There has been remarkable progress, however, in the instrumentation of liquid chromatography (LC) and mass spectrometry (MS) (LCMS), experimental paradigms and bioinformatics of the proteome. Here, we present a summary of methodological innovations of recent years in MS based proteomics and the power of new generation proteomics, review proteomics studies that have been conducted in schizophrenia to date, and propose how such data can be analyzed and integrated with other omics results. The function of a protein is determined by multiple molecular properties, i.e., subcellular localization, posttranslational modification (PTMs) and protein-protein interactions (PPIs). Incorporation of these properties poses additional challenges in proteomics and their integration with other omics; yet is a critical next step to close the loop of multi-omics integration. In sum, the recent advent of high-throughput proteome characterization technologies and novel mathematical approaches enable us to incorporate functional properties of the proteome to offer a comprehensive multi-omics based understanding of schizophrenia pathophysiology.

Phosphoproteomic analysis of protease-activated receptor-1 biased signaling reveals unique modulators of endothelial barrier function

Thrombin, a procoagulant protease, cleaves and activates protease-activated receptor-1 (PAR1) to promote inflammatory responses and endothelial dysfunction. In contrast, activated protein C (APC), an anticoagulant protease, activates PAR1 through a distinct cleavage site and promotes anti-inflammatory responses, prosurvival, and endothelial barrier stabilization. The distinct tethered ligands formed through cleavage of PAR1 by thrombin versus APC result in unique active receptor conformations that bias PAR1 signaling. Despite progress in understanding PAR1 biased signaling, the proteins and pathways utilized by thrombin versus APC signaling to induce opposing cellular functions are largely unknown. Here, we report the global phosphoproteome induced by thrombin and APC signaling in endothelial cells with the quantification of 11,266 unique phosphopeptides using multiplexed quantitative mass spectrometry. Our results reveal unique dynamic phosphoproteome profiles of thrombin and APC signaling, an enrichment of associated biological functions, including key modulators of endothelial barrier function, regulators of gene transcription, and specific kinases predicted to mediate PAR1 biased signaling. Using small interfering RNA to deplete a subset of phosphorylated proteins not previously linked to thrombin or APC signaling, a function for afadin and adducin-1 actin binding proteins in thrombin-induced endothelial barrier disruption is unveiled. Afadin depletion resulted in enhanced thrombin-promoted barrier permeability, whereas adducin-1 depletion completely ablated thrombin-induced barrier disruption without compromising p38 signaling. However, loss of adducin-1 blocked APC-induced Akt signaling. These studies define distinct thrombin and APC dynamic signaling profiles and a rich array of proteins and biological pathways that engender PAR1 biased signaling in endothelial cells.

Protein Biomarker Quantification by Immunoaffinity Liquid Chromatography–Tandem Mass Spectrometry: Current State and Future Vision

Immunoaffinity–mass spectrometry (IA-MS) is an emerging analytical genre with several advantages for profiling and determination of protein biomarkers. Because IA-MS combines affinity capture, analogous to ligand binding assays (LBAs), with mass spectrometry (MS) detection, this platform is often described using the term hybrid methods. The purpose of this report is to provide an overview of the principles of IA-MS and to demonstrate, through application, the unique power and potential of this technology. By combining target immunoaffinity enrichment with the use of stable isotope-labeled internal standards and MS detection, IA-MS achieves high sensitivity while providing unparalleled specificity for the quantification of protein biomarkers in fluids and tissues. In recent years, significant uptake of IA-MS has occurred in the pharmaceutical industry, particularly in the early stages of clinical development, enabling biomarker measurement previously considered unattainable. By comparison, IA-MS adoption by CLIA laboratories has occurred more slowly. Current barriers to IA-MS use and opportunities for expanded adoption are discussed. The path forward involves identifying applications for which IA-MS is the best option compared with LBA or MS technologies alone. IA-MS will continue to benefit from advances in reagent generation, more sensitive and higher throughput MS technologies, and continued growth in use by the broader analytical community. Collectively, the pursuit of these opportunities will secure expanded long-term use of IA-MS for clinical applications.

Phosphoproteomics Profiling of Cotton (Gossypium hirsutum L.) Roots in Response to Verticillium dahliae Inoculation

Verticillium wilt is a plant vascular disease causing severe yield and quality losses in many crops and is caused by the soil-borne plant pathogenic fungus Verticillium dahliae. To investigate the molecular mechanisms of the cotton-V. dahliae interaction, a time-course phosphoproteomic analysis of roots of susceptible and resistant cotton lines in response to V. dahliae was performed. In total, 1716 unique phosphoproteins were identified in the susceptible (S) and resistant (R) cotton lines. Of these, 359 phosphoproteins were significantly different in R1 (1 day after V. dahliae inoculation) vs R0 (mock) group and 287 phosphoproteins in R2 (3 days after V. dahliae inoculation) vs R0 group. Moreover, 263 proteins of V. dahliae-regulated phosphoproteins were significantly changed in S1 (1 day after V. dahliae inoculation) vs S0 (mock) group and 197 proteins in S2 (3 days after V. dahliae inoculation) vs S0 group. Thirty phosphoproteins were significantly changed and common to the resistant and susceptible cotton lines following inoculation with V. dahliae. Specifically, 92 phosphoproteins were shared in both in R1 vs R0 and R2 vs R0 but not in susceptible cotton lines. There were 38 common phosphoproteins shared in both S1 vs S0 and S2 vs S0 but not in resistant cotton lines. GO terms and Kyoto Encyclopedia of Genes and Genomes pathway analyses displayed an abundance of known and novel phosphoproteins related to plant-pathogen interactions, signal transduction, and metabolic processes, which were correlated with resistance against fungal infection. These data provide new perspectives and inspiration for understanding molecular defense mechanisms of cotton roots against V. dahliae infection.

Mass Spectrometry-Based Analysis of Time-Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time-dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners-both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS-based analysis of time-resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.

Systems-level Analysis Reveals Multiple Modulators of Epithelial-mesenchymal Transition and Identifies DNAJB4 and CD81 as Novel Metastasis Inducers in Breast Cancer

Epithelial-mesenchymal transition (EMT) is driven by complex signaling events that induce dramatic biochemical and morphological changes whereby epithelial cells are converted into cancer cells. However, the underlying molecular mechanisms remain elusive. Here, we used mass spectrometry based quantitative proteomics approach to systematically analyze the post-translational biochemical changes that drive differentiation of human mammary epithelial (HMLE) cells into mesenchymal. We identified 314 proteins out of more than 6,000 unique proteins and 871 phosphopeptides out of more than 7,000 unique phosphopeptides as differentially regulated. We found that phosphoproteome is more unstable and prone to changes during EMT compared with the proteome and multiple alterations at proteome level are not thoroughly represented by transcriptional data highlighting the necessity of proteome level analysis. We discovered cell state specific signaling pathways, such as Hippo, sphingolipid signaling, and unfolded protein response (UPR) by modeling the networks of regulated proteins and potential kinase-substrate groups. We identified two novel factors for EMT whose expression increased on EMT induction: DnaJ heat shock protein family (Hsp40) member B4 (DNAJB4) and cluster of differentiation 81 (CD81). Suppression of DNAJB4 or CD81 in mesenchymal breast cancer cells resulted in decreased cell migration in vitro and led to reduced primary tumor growth, extravasation, and lung metastasis in vivo Overall, we performed the global proteomic and phosphoproteomic analyses of EMT, identified and validated new mRNA and/or protein level modulators of EMT. This work also provides a unique platform and resource for future studies focusing on metastasis and drug resistance.

Proteomic Analysis of Human Plasma during Intermittent Fasting

Intermittent fasting (IF) increases lifespan and decreases metabolic disease phenotypes and cancer risk in model organisms, but the health benefits of IF in humans are less clear. Human plasma derived from clinical trials is one of the most difficult sample sets to analyze using mass spectrometry-based proteomics due to the extensive sample preparation required and the need to process many samples to achieve statistical significance. Here, we describe an optimized and accessible device (Spin96) to accommodate up to 96 StageTips, a widely used sample preparation medium enabling efficient and consistent processing of samples prior to LC-MS/MS. We have applied this device to the analysis of human plasma from a clinical trial of IF. In this longitudinal study employing 8-weeks IF, we identified significant abundance differences induced by the IF intervention, including increased apolipoprotein A4 (APOA4) and decreased apolipoprotein C2 (APOC2) and C3 (APOC3). These changes correlated with a significant decrease in plasma triglycerides after the IF intervention. Given that these proteins have a role in regulating apolipoprotein particle metabolism, we propose that IF had a positive effect on lipid metabolism through modulation of HDL particle size and function. In addition, we applied a novel human protein variant database to detect common protein variants across the participants. We show that consistent detection of clinically relevant peptides derived from both alleles of many proteins is possible, including some that are associated with human metabolic phenotypes. Together, these findings illustrate the power of accessible workflows for proteomics analysis of clinical samples to yield significant biological insight.

Quantitative proteomic analyses of dynamic signalling events in cortical neurons undergoing excitotoxic cell death

Excitotoxicity, caused by overstimulation or dysregulation of ionotropic glutamate receptors (iGluRs), is a pathological process directing neuronal death in many neurological disorders. The aberrantly stimulated iGluRs direct massive influx of calcium ions into the affected neurons, leading to changes in expression and phosphorylation of specific proteins to modulate their functions and direct their participation in the signalling pathways that induce excitotoxic neuronal death. To define these pathways, we used quantitative proteomic approaches to identify these neuronal proteins (referred to as the changed proteins) and determine how their expression and/or phosphorylation dynamically changed in association with excitotoxic cell death. Our data, available in ProteomeXchange with identifier PXD008353, identified over 100 changed proteins exhibiting significant alterations in abundance and/or phosphorylation levels at different time points (5–240 min) in neurons after glutamate overstimulation. Bioinformatic analyses predicted that many of them are components of signalling networks directing defective neuronal morphology and functions. Among them, the well-known neuronal survival regulators including mitogen-activated protein kinases Erk1/2, glycogen synthase kinase 3 (GSK3) and microtubule-associated protein (Tau), were selected for validation by biochemical approaches, which confirmed the findings of the proteomic analysis. Bioinformatic analysis predicted Protein Kinase B (Akt), c-Jun kinase (JNK), cyclin-dependent protein kinase 5 (Cdk5), MAP kinase kinase (MEK), Casein kinase 2 (CK2), Rho-activated protein kinase (Rock) and Serum/glucocorticoid-regulated kinase 1 (SGK1) as the potential upstream kinases phosphorylating some of the changed proteins. Further biochemical investigation confirmed the predictions of sustained changes of the activation states of neuronal Akt and CK2 in excitotoxicity. Thus, future investigation to define the signalling pathways directing the dynamic alterations in abundance and phosphorylation of the identified changed neuronal proteins will help elucidate the molecular mechanism of neuronal death in excitotoxicity.

Integrating phosphoproteomics into kinase-targeted cancer therapies in precision medicine

Protein phosphorylation is a post-translational modification that is involved in the regulation of all major biological processes in cells. As a rapid and reversible means to modulate protein activity and transduce signals, aberrant protein phosphorylation is implicated in the onset and progression of most cancer types. Therefore, pharmacological inhibitors against protein kinases are highly pursued therapeutic approaches for treating cancer. Phosphoproteomics has become an important approach for investigating protein phosphorylation, and it is a technique that provides measurements of kinase pathway activation and the circuitry of signalling networks with both spatial and temporal resolution. Combined with the recent advances in mass spectrometry and development in biochemical procedures for phosphopeptide enrichment and computational approaches, high-throughput phosphoproteomics enables the investigation of kinase signalling networks with unprecedented depth. Here, we review the recent progresses in phosphoproteomics methodology and how phosphoproteomics profiling could be implemented in translational research to aid cancer therapies, facilitate novel drug target discovery and overcome the therapeutic obstacles caused by drug resistance. SIGNIFICANCE: In this review, we summarized the recent progress in mass spectrometry-based phosphoproteomics and discussed how phosphoproteomics profiling can be implemented in translational research to aid cancer therapies, facilitate novel drug target discovery and overcome the therapeutic obstacles caused by drug resistance due to the rapid remodelling of signalling networks in response to kinase inhibitor treatment. In addition, we addressed the insights and challenges of applying MS phosphoproteomics in clinical routine practice in precision medicine. This review will help readers become more familiar with the recent advancements and applications of phosphoproteomics, especially in the field of kinase-targeted cancer therapy.

PaDuA: A Python Library for High-Throughput (Phospho)proteomics Data Analysis

The increased speed and sensitivity in mass spectrometry-based proteomics has encouraged its use in biomedical research in recent years. Large-scale detection of proteins in cells, tissues, and whole organisms yields highly complex quantitative data, the analysis of which poses significant challenges. Standardized proteomic workflows are necessary to ensure automated, sharable, and reproducible proteomics analysis. Likewise, standardized data processing workflows are also essential for the overall reproducibility of results. To this purpose, we developed PaDuA, a Python package optimized for the processing and analysis of (phospho)proteomics data. PaDuA provides a collection of tools that can be used to build scripted workflows within Jupyter Notebooks to facilitate bioinformatics analysis by both end-users and developers.

Middle-down approach: a choice to sequence and characterize proteins/proteomes by mass spectrometry

Owing to rapid growth in the elucidation of genome sequences of various organisms, deducing proteome sequences has become imperative, in order to have an improved understanding of biological processes. Since the traditional Edman method was unsuitable for high-throughput sequencing and also for N-terminus modified proteins, mass spectrometry (MS) based methods, mainly based on soft ionization modes: electrospray ionization and matrix-assisted laser desorption/ionization, began to gain significance. MS based methods were adaptable for high-throughput studies and applicable for sequencing N-terminus blocked proteins/peptides too. Consequently, over the last decade a new discipline called 'proteomics' has emerged, which encompasses the attributes necessary for high-throughput identification of proteins. 'Proteomics' may also be regarded as an offshoot of the classic field, 'biochemistry'. Many protein sequencing and proteomic investigations were successfully accomplished through MS dependent sequence elucidation of 'short proteolytic peptides (typically: 7-20 amino acid residues), which is called the 'shotgun' or 'bottom-up (BU)' approach. While the BU approach continues as a workhorse for proteomics/protein sequencing, attempts to sequence intact proteins without proteolysis, called the 'top-down (TD)' approach started, due to ambiguities in the BU approach, e.g., protein inference problem, identification of proteoforms and the discovery of posttranslational modifications (PTMs). The high-throughput TD approach (TD proteomics) is yet in its infancy. Nevertheless, TD characterization of purified intact proteins has been useful for detecting PTMs. With the hope to overcome the pitfalls of BU and TD strategies, another concept called the 'middle-down (MD)' approach was put forward. Similar to BU, the MD approach also involves proteolysis, but in a restricted manner, to produce 'longer' proteolytic peptides than the ones usually obtained in BU studies, thereby providing better sequence coverage. In this regard, special proteases (OmpT, Sap9, IdeS) have been used, which can cleave proteins to produce longer proteolytic peptides. By reviewing ample evidences currently existing in the literature that is predominantly on PTM characterization of histones and antibodies, herein we highlight salient features of the MD approach. Consequently, we are inclined to claim that the MD concept might have widespread applications in future for various research areas, such as clinical, biopharmaceuticals (including PTM analysis) and even for general/routine characterization of proteins including therapeutic proteins, but not just limited to analysis of histones or antibodies.

Arenobufagin induces MCF-7 cell apoptosis by promoting JNK-mediated multisite phosphorylation of Yes-associated protein

Background

It has been demonstrated that bufadienolides exert potent anti-cancer activity in various tumor types. However, the mechanisms that underlie their anti-cancer properties remain unclear. Yes-associated protein, a key effector of Hippo signaling, functions as a transcription coactivator, plays oncogenic and tumor suppressor roles under different conditions. Here, we report that arenobufagin (ABF), a representative bufadienolide, induced breast cancer MCF-7 cells to undergo apoptosis, which occurred through the JNK-mediated multisite phosphorylation of YAP.

Methods

Cytotoxicity was examined using an MTT assay. ABF-induced apoptosis was measured with a TUNEL assay and Annexin V-FITC/PI double staining assay. Western blotting, immunofluorescence, qRT-PCR and coimmunoprecipitation were employed to assess the expression levels of the indicated molecules. Lose-of-function experiments were carried out with siRNA transfection and pharmacological inhibitors. ABF-induced phosphopeptides were enriched with Ti4⁺-IMAC chromatography and further subjected to reverse-phase nano-LC–MS/MS analysis.

Results

ABF significantly reduced the viability of MCF-7 cells and increased the percentage of early and late apoptotic cells in a concentration- and time-dependent manner. Following ABF treatment, YAP accumulated in the nucleus and bound to p73, which enhanced the transcription of the pro-apoptotic genes Bax and p53AIP1. YAP knock-down significantly attenuated ABF-induced apoptotic cell death. Importantly, we found that the mobility shift of YAP was derived from its phosphorylation at multiple sites, including Tyr357. Moreover, mass spectrometry analysis identified 19 potential phosphorylation sites in YAP, with a distribution of 14 phosphoserine and 5 phosphothreonine residues. Furthermore, we found that the JNK inhibitor SP600125 completely diminished the mobility shift of YAP and its phosphorylation at Tyr357, the binding of YAP and p73, the transcription of Bax and p53AIP1 as well as the apoptosis induced by ABF. These data indicate that ABF induced YAP multisite phosphorylation, which was associated with p73 binding, and that apoptosis was mediated by the JNK signaling pathway.

Conclusions

Our data demonstrate that ABF suppresses MCF-7 breast cancer proliferation by triggering the pro-apoptotic activity of YAP, which is mediated by JNK signaling-induced YAP multisite phosphorylation as well as its association with p73. The present work not only provides additional information on the use of ABF as an anti-breast cancer drug, but also offers evidence that the induction of the tumor suppressor role of YAP may be a therapeutic strategy.

Electronic supplementary material

The online version of this article (10.1186/s12935-018-0706-9) contains supplementary material, which is available to authorized users.

In vivo phosphoproteomics reveals kinase activity profiles that predict treatment outcome in triple-negative breast cancer

Triple-negative breast cancer (TNBC) lacks prognostic and predictive markers. Here, we use high-throughput phosphoproteomics to build a functional TNBC taxonomy. A cluster of 159 phosphosites is upregulated in relapsed cases of a training set (n = 34 patients), with 11 hyperactive kinases accounting for this phosphoprofile. A mass-spectrometry-to-immunohistochemistry translation step, assessing 2 independent validation sets, reveals 6 kinases with preserved independent prognostic value. The kinases split the validation set into two patterns: one without hyperactive kinases being associated with a >90% relapse-free rate, and the other one showing ≥1 hyperactive kinase and being associated with an up to 9.5-fold higher relapse risk. Each kinase pattern encompasses different mutational patterns, simplifying mutation-based taxonomy. Drug regimens designed based on these 6 kinases show promising antitumour activity in TNBC cell lines and patient-derived xenografts. In summary, the present study elucidates phosphosites and kinases implicated in TNBC and suggests a target-based clinical classification system for TNBC.

Triple-negative breast cancer (TNBC) lacks prognostic and predictive markers. Here, the authors use phosphoproteomics to define kinases with distinct activity profiles in TNBC, demonstrating their prognostic value as well as their utility for simplifying TNBC classification and designing drug regimens.

A Methodological Assessment and Characterization of Genetically-Driven Variation in Three Human Phosphoproteomes

Phosphorylation of proteins on serine, threonine, and tyrosine residues is a ubiquitous post-translational modification that plays a key part of essentially every cell signaling process. It is reasonable to assume that inter-individual variation in protein phosphorylation may underlie phenotypic differences, as has been observed for practically any other molecular regulatory phenotype. However, we do not know much about the extent of inter-individual variation in phosphorylation because it is quite challenging to perform a quantitative high throughput study to assess inter-individual variation in any post-translational modification. To test our ability to address this challenge with SILAC-based mass spectrometry, we quantified phosphorylation levels for three genotyped human cell lines within a nested experimental framework, and found that genetic background is the primary determinant of phosphoproteome variation. We uncovered multiple functional, biophysical, and genetic associations with germline driven phosphopeptide variation. Variants affecting protein levels or structure were among these associations, with the latter presenting, on average, a stronger effect. Interestingly, we found evidence that is consistent with a phosphopeptide variability buffering effect endowed from properties enriched within longer proteins. Because the small sample size in this 'pilot' study may limit the applicability of our genetic observations, we also undertook a thorough technical assessment of our experimental workflow to aid further efforts. Taken together, these results provide the foundation for future work to characterize inter-individual variation in post-translational modification levels and reveal novel insights into the nature of inter-individual variation in phosphorylation.

CTGF/VEGFA-activated Fibroblasts Promote Tumor Migration Through Micro-environmental Modulation

Fibroblast activation is associated with tumor progression and implicated in metastasis, but the initial triggering signals required to kick-start this process remain largely unknown. Because small cancerous lesions share limited physical contact with neighboring fibroblasts, we reasoned the first tumor-derived signal for fibroblast activation should be secreted and diffusible. By pulsed metabolic labeling and click-chemistry based affinity enrichment, we sieved through the ductal carcinoma secretome for potential fibroblast activators. Using immuno-depletion/supplementation assays on various secreted factors, we pinpointed that tumor-secreted CTGF/VEGFA alone is sufficient to activate paired mammary fibroblasts from the same patient via ROCK1 and JunB signaling. Fibroblasts activated in this manner are distinct in morphology, growth, and adopt a highly tumor-like secretion profile, which in turn promotes tumor migration by counteracting oxidative and lactate stress. These findings reveal a profound division-of-labor between normal and cancer cells under the directive of the latter, and allude to potential metastatic prevention through inhibiting local fibroblast activation.

Label-Free Quantitative Phosphoproteomics Reveals Regulation of Vasodilator-Stimulated Phosphoprotein upon Stathmin-1 Silencing in a Pair of Isogenic Colorectal Cancer Cell Lines

In this communication, we present the phosphoproteome changes in an isogenic pair of colorectal cancer cell lines, viz., the poorly metastatic HCT-116 and the highly metastatic derivative E1, upon stathmin-1 (STMN1) knockdown. The aim was to better understand how the alterations of the phosphoproteins in these cells are involved in cancer metastasis. After the phosphopeptides were enriched using the TiO₂ HAMMOC approach, comparative proteomics analysis was carried out using sequential window acquisition of all theoretical mass spectra-MS. Following bioinformatics analysis using MarkerView and OneOmics platforms, we identified a list of regulated phosphoproteins that may play a potential role in signaling, maintenance of cytoskeletal structure, and focal adhesion. Among these phosphoproteins, was the actin cytoskeleton regulator protein, vasodilator-stimulated phosphoprotein (VASP), where its change in phosphorylation status was found to be concomitant with STMN1-associated roles in metastasis. We further showed that silencing of stathmin-1 altered the expression, subcellular localization and phosphorylation status of VASP, which suggested that it might be associated with remodeling of the cell cytoskeleton in colorectal cancer metastasis.

Design and Profiling of a Subcellular Targeted Optogenetic cAMP-Dependent Protein Kinase

Although the cAMP-dependent protein kinase (PKA) is ubiquitously expressed, it is sequestered at specific subcellular locations throughout the cell, thereby resulting in compartmentalized cellular signaling that triggers site-specific behavioral phenotypes. We developed a three-step engineering strategy to construct an optogenetic PKA (optoPKA) and demonstrated that, upon illumination, optoPKA migrates to specified intracellular sites. Furthermore, we designed intracellular spatially segregated reporters of PKA activity and confirmed that optoPKA phosphorylates these reporters in a light-dependent fashion. Finally, proteomics experiments reveal that light activation of optoPKA results in the phosphorylation of known endogenous PKA substrates as well as potential novel substrates.

Advances in microscale separations towards nanoproteomics applications

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. However, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1μg total proteins (e.g., cellular heterogeneity in tissue pathologies). Herein, we review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, and their contributions towards nanoproteomics applications.

Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells

Cellular signaling, predominantly mediated by phosphorylation through protein kinases, is found to be deregulated in most cancers. Accordingly, protein kinases have been subject to intense investigations in cancer research, to understand their role in oncogenesis and to discover new therapeutic targets. Despite great advances, an understanding of kinase dysfunction in cancer is far from complete.A powerful tool to investigate phosphorylation is mass-spectrometry (MS)-based phosphoproteomics, which enables the identification of thousands of phosphorylated peptides in a single experiment. Since every phosphorylation event results from the activity of a protein kinase, high-coverage phosphoproteomics data should indirectly contain comprehensive information about the activity of protein kinases.In this chapter, we discuss the use of computational methods to predict kinase activity scores from MS-based phosphoproteomics data. We start with a short explanation of the fundamental features of the phosphoproteomics data acquisition process from the perspective of the computational analysis. Next, we briefly review the existing databases with experimentally verified kinase-substrate relationships and present a set of bioinformatic tools to discover novel kinase targets. We then introduce different methods to infer kinase activities from phosphoproteomics data and these kinase-substrate relationships. We illustrate their application with a detailed protocol of one of the methods, KSEA (Kinase Substrate Enrichment Analysis). This method is implemented in Python within the framework of the open-source Kinase Activity Toolbox (kinact), which is freely available at http://github.com/saezlab/kinact/ .

Post-Translational Peptide Splicing and T Cell Responses

CD8⁺ T cell specificity depends on the recognition of MHC class I-epitope complexes at the cell surface. These epitopes are mainly produced via degradation of proteins by the proteasome, generating fragments of the original sequence. However, it is now clear that proteasomes can produce a significant portion of epitopes by reshuffling the antigen sequence, thus expanding the potential antigenic repertoire. MHC class I-restricted spliced epitopes have been described in tumors and infections, suggesting an unpredicted relevance of these peculiar peptides. We review current knowledge about proteasome-catalyzed peptide splicing (PCPS), the emerging rules governing this process, and the potential implications for our understanding and therapeutic use of CD8⁺ T cells, as well as mechanisms generating other non-canonical antigenic epitopes targeted by the T cell response.

Kinase activity ranking using phosphoproteomics data (KARP) quantifies the contribution of protein kinases to the regulation of cell viability

Cell survival is regulated by a signaling network driven by the activity of protein kinases; however, determining the contribution that each kinase in the network makes to such regulation remains challenging. Here, we report a computational approach that uses mass spectrometry-based phosphoproteomics data to rank protein kinases based on their contribution to cell regulation. We found that the scores returned by this algorithm, which we have termed kinase activity ranking using phosphoproteomics data (KARP), were a quantitative measure of the contribution that individual kinases make to the signaling output. Application of KARP to the analysis of eight hematological cell lines revealed that cyclin-dependent kinase (CDK) 1/2, casein kinase (CK) 2, extracellular signal-related kinase (ERK), and p21-activated kinase (PAK) were the most frequently highly ranked kinases in these cell models. The patterns of kinase activation were cell-line specific yet showed a significant association with cell viability as a function of kinase inhibitor treatment. Thus, our study exemplifies KARP as an untargeted approach to empirically and systematically identify regulatory kinases within signaling networks.

Analyses of PDE-regulated phosphoproteomes reveal unique and specific cAMP-signaling modules in T cells

Specific functions for different cyclic nucleotide phosphodiesterases (PDEs) have not yet been identified in most cell types. Conventional approaches to study PDE function typically rely on measurements of global cAMP, general increases in cAMP-dependent protein kinase (PKA), or the activity of exchange protein activated by cAMP (EPAC). Although newer approaches using subcellularly targeted FRET reporter sensors have helped define more compartmentalized regulation of cAMP, PKA, and EPAC, they have limited ability to link this regulation to downstream effector molecules and biological functions. To address this problem, we have begun to use an unbiased mass spectrometry-based approach coupled with treatment using PDE isozyme-selective inhibitors to characterize the phosphoproteomes of the functional pools of cAMP/PKA/EPAC that are regulated by specific cAMP-PDEs (the PDE-regulated phosphoproteomes). In Jurkat cells we find multiple, distinct PDE-regulated phosphoproteomes that can be defined by their responses to different PDE inhibitors. We also find that little phosphorylation occurs unless at least two different PDEs are concurrently inhibited in these cells. Moreover, bioinformatics analyses of these phosphoproteomes provide insight into the unique functional roles, mechanisms of action, and synergistic relationships among the different PDEs that coordinate cAMP-signaling cascades in these cells. The data strongly suggest that the phosphorylation of many different substrates contributes to cAMP-dependent regulation of these cells. The findings further suggest that the approach of using selective, inhibitor-dependent phosphoproteome analysis can provide a generalized methodology for understanding the roles of different PDEs in the regulation of cyclic nucleotide signaling.

Phosphoproteomics with Activated Ion Electron Transfer Dissociation

The ability to localize phosphosites to specific amino acid residues is crucial to translating phosphoproteomic data into biological meaningful contexts. In a companion manuscript ( Anal. Chem. 2017 , DOI: 10.1021/acs.analchem.7b00213 ), we described a new implementation of activated ion electron transfer dissociation (AI-ETD) on a quadrupole-Orbitrap-linear ion trap hybrid MS system (Orbitrap Fusion Lumos), which greatly improved peptide fragmentation and identification over ETD and other supplemental activation methods. Here we present the performance of AI-ETD for identifying and localizing sites of phosphorylation in both phosphopeptides and intact phosphoproteins. Using 90 min analyses we show that AI-ETD can identify 24,503 localized phosphopeptide spectral matches enriched from mouse brain lysates, which more than triples identifications from standard ETD experiments and outperforms ETcaD and EThcD as well. AI-ETD achieves these gains through improved quality of fragmentation and MS/MS success rates for all precursor charge states, especially for doubly protonated species. We also evaluate the degree to which phosphate neutral loss occurs from phosphopeptide product ions due to the infrared photoactivation of AI-ETD and show that modifying phosphoRS (a phosphosite localization algorithm) to include phosphate neutral losses can significantly improve localization in AI-ETD spectra. Finally, we demonstrate the utility of AI-ETD in localizing phosphosites in α-casein, an ∼23.5 kDa phosphoprotein that showed eight of nine known phosphorylation sites occupied upon intact mass analysis. AI-ETD provided the greatest sequence coverage for all five charge states investigated and was the only fragmentation method to localize all eight phosphosites for each precursor. Overall, this work highlights the analytical value AI-ETD can bring to both bottom-up and top-down phosphoproteomics.

Label-Free Phosphoproteomic Approach for Kinase Signaling Analysis

Phosphoproteomics is a powerful platform for the unbiased profiling of kinase-driven signaling pathways. Quantitation of phosphorylation can be performed by means of either labeling or label-free mass spectrometry (MS) methods. Because of their simplicity and universality, label-free methodology is gaining acceptance and popularity in molecular biology research. Analytical workflows for label-free quantification of phosphorylation, however, need to overcome several hurdles for the technique to be accurate and precise. These include the use of biochemical extraction procedures that efficiently and reproducibly isolate phosphopeptides from complex peptide matrices and an analytical strategy that can cope with missing MS/MS phosphopeptide spectra in a subset of the samples being compared. Testing the accuracy of the developed workflows is an essential prerequisite in the analysis of small molecules by MS, and this is achieved by constructing calibration curves to demonstrate linearity of quantification for each analyte. This level of analytical rigor is rarely shown in large-scale quantification of proteins using either label-based or label-free techniques. In this chapter we show an approach to test linearity of quantification of each phosphopeptide quantified by liquid chromatography (LC)-MS without the need to synthesize standards or label proteins. We further describe the appropriate sample handling techniques required for the reproducible recovery of phosphopeptides and explore the essential algorithmic features that enable the handling of missing MS/MS spectra and thus make label-free data suitable for such analyses. The combined technology described in this chapter expands the applicability of phosphoproteomics to questions not previously tractable with other methodologies.

Insights into chemoselectivity principles in metal oxide affinity chromatography using tailored nanocast metal oxide microspheres and mass spectrometry-based phosphoproteomics

Custom-made nanocast metal oxide materials provide new insights into the mechanisms of metal oxide affinity chromatography, a method widely used to study proteome-wide protein phosphorylation.

The current state of the art of quantitative phosphoproteomics and its applications to diabetes research

Protein phosphorylation is a fundamental regulatory mechanism in many cellular processes and aberrant perturbation of phosphorylation has been implicated in various human diseases. Kinases and their cognate inhibitors have been considered as hotspots for drug development. Therefore, the emerging tools, which enable a system-wide quantitative profiling of phosphoproteome, would offer a powerful impetus in unveiling novel signaling pathways, drug targets and/or biomarkers for diseases of interest. This review highlights recent advances in phosphoproteomics, the current state of the art of the technologies and the challenges and future perspectives of this research area. Finally, some exemplary applications of phosphoproteomics in diabetes research are underscored.

Taking the stock of granule cargo: Platelet releasate proteomics

Human platelets are key players in a multitude of physiological and pathological processes. Upon activation they release cargo from different types of granules as well as microparticles in an apparently well-regulated and orchestrated manner. The resulting specific platelet releasates create microenvironments of biologically active compounds and proteins during platelet aggregation and thrombus formation, allowing efficient delivery of growth factors and immune modulators to their sites of effect and enhancing the coagulative response in a positive feedback loop. Thus, platelet releasates play a central role in the regulation of platelet homeostasis and heterotypic cell interaction. Additionally, it recently emerged that both the qualitative and quantitative composition of the releasate as well as release dynamics may be stimulus dependent and therefore more complex than expected. Mass spectrometry-based proteomics is an important asset for studying platelet releasates in vitro, as it allows not only (i) identifying released proteins, but moreover (ii) determining their quantities and the dynamics of release as well as (iii) differentially comparing releasates across a variety of conditions. Though owing to the high sensitivity and comprehensiveness of modern proteomic techniques, a thorough experimental design and a standardized and robust sample preparation are essential to obtain highly confident and reliable insights into platelet biology and pathology. Here, we review releasate proteome studies and crucial sample preparation strategies to summarize possible achievements of state-of-the-art technologies and furthermore discuss potential pitfalls and limitations. We provide a future perspective of platelet releasate proteomics including targeted analyses, post-translational modifications and multi-omics approaches that should be adopted by platelet releasate researchers due to their tremendous depth and comprehensiveness.