Mapping in vivo signal transduction defects by phosphoproteomics

Synergistic optimization of Liquid Chromatography and Mass Spectrometry parameters on Orbitrap Tribrid mass spectrometer for high efficient data-dependent proteomics

Steady improvement in Orbitrap-based mass spectrometry (MS) technologies has greatly advanced the peptide sequencing speed and depth. In-depth analysis of the performance of state-of-the-art MS and optimization of key parameters can improve sequencing efficiency. In this study, we first systematically compared the performance of two popular data-dependent acquisition approaches, with Orbitrap as the first-stage (MS1) mass analyzer and the same Orbitrap (high-high approach) or ion trap (high-low approach) as the second-stage (MS2) mass analyzer, on the Orbitrap Fusion mass spectrometer. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. However, regardless of the acquisition method, there are still more than 60% of peptide features untargeted for MS2 scan. We then systematically optimized the MS parameters using the high-high approach. Increasing the isolation window in the high-high approach could facilitate faster scan speed, but decreased MS2 identification rate. On the contrary, increasing the injection time of MS2 scan could increase identification rate but decrease scan speed and the number of identified MS2 spectra. Dynamic exclusion time should be set properly according to the chromatography peak width. Furthermore, we found that the Orbitrap analyzer, rather than the analytical column, was easily saturated with higher loading amount, thus limited the dynamic range of MS1-based quantification. By using optimized parameters, 10 000 proteins and 110 000 unique peptides were identified by using 20 h of effective liquid chromatography (LC) gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor ion targeting, fragment ion detection, and chromatographic separation for high efficient data-dependent proteomics.

Simplifying the Proteome: Analytical Strategies for Improving Peak Capacity

The diversity of biological samples and dynamic range of analytes being analyzed can prove to be an analytical challenge and is particularly prevalent to proteomic studies. Maximizing the peak capacity of the workflow employed can extend the dynamic range and increase identification rates. The focus of this chapter is to present means of achieving this for various analytical techniques such as liquid chromatography, mass spectrometry and ion mobility. A combination of these methods can be used as part of a data independent acquisition strategy, thereby limiting issues such as chimericy when analyzing regions of extreme analyte density.

MAPK pathway and B cells overactivation in multiple sclerosis revealed by phosphoproteomics and genomic analysis

Dysregulation of signaling pathways in multiple sclerosis (MS) can be analyzed by phosphoproteomics in peripheral blood mononuclear cells (PBMCs). We performed in vitro kinetic assays on PBMCs in 195 MS patients and 60 matched controls and quantified the phosphorylation of 17 kinases using xMAP assays. Phosphoprotein levels were tested for association with genetic susceptibility by typing 112 single-nucleotide polymorphisms (SNPs) associated with MS susceptibility. We found increased phosphorylation of MP2K1 in MS patients relative to the controls. Moreover, we identified one SNP located in the PHDGH gene and another on IRF8 gene that were associated with MP2K1 phosphorylation levels, providing a first clue on how this MS risk gene may act. The analyses in patients treated with disease-modifying drugs identified the phosphorylation of each receptor's downstream kinases. Finally, using flow cytometry, we detected in MS patients increased STAT1, STAT3, TF65, and HSPB1 phosphorylation in CD19⁺ cells. These findings indicate the activation of cell survival and proliferation (MAPK), and proinflammatory (STAT) pathways in the immune cells of MS patients, primarily in B cells. The changes in the activation of these kinases suggest that these pathways may represent therapeutic targets for modulation by kinase inhibitors.

Utilization of Proteomic Technologies for Precision Oncology Applications

Genomic analysis of tumor specimens has revealed that cancer is fundamentally a proteomic disease at the functional level: driven by genomically defined derangements, but selected for in the proteins that are encoded and the aberrant activation of signaling and biochemical networks. This activation is measured by posttranslational modifications such as phosphorylation and other modifications that modulate cellular signaling, and these events cannot be effectively measured by genomic analysis alone. Moreover, these signaling networks by and large represent the targets for many FDA-approved and experimental molecularly targeted therapeutics. Consequently, it is important that we consider new classification schemas for oncology based not on tumor site of origin or histology under the microscope but on the functional protein signaling architecture. There are numerous proteomic technologies that could be discussed from a purely technological standpoint, but this chapter will concentrate on an overview of the main proteomic technologies available for conducting protein pathway activation analysis of clinical specimens such as multiplex immunoassays, phospho-specific flow cytometry, reverse phase protein microarrays, quantitative immunohistochemistry, and mass spectrometry. This chapter will focus on the application of these technologies to cancer-based clinical studies evaluating prognostic/predictive markers or for stratifying patients to personalized treatments.

Quantitative Phosphoproteome Analysis of Clostridioides difficile Toxin B Treated Human Epithelial Cells

The large clostridial glucosylating toxin B (TcdB) is a major virulence factor of the nosocomial pathogen Clostridioides difficile. TcdB inhibits small GTPases by glucosylation leading to impaired downstream signaling. TcdB also possesses a glucosyltransferase independent effect described as pyknosis. To elucidate the impact of TcdB and its glucosylation-inactive mutant TcdB_NXN on the kinome of human cells, SILAC labeled HEp-2 cells were treated with 2 nM TcdB for 8 h. Phosphopeptides were enriched using SCX chromatography, IMAC and TiO₂ followed shotgun mass spectrometry analysis. Overall 4,197 phosphopeptides were identified; more than 1,200 phosphosites responded to treatment with TcdB or TcdB_NXN. The data suggested that predominantly stress-activated MAPK-dependent signaling pathways were triggered by toxin B treatment.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Construction and Deciphering of Human Phosphorylation-Mediated Signaling Transduction Networks

Protein phosphorylation is the most abundant reversible covalent modification. Human protein kinases participate in almost all biological pathways, and approximately half of the kinases are associated with disease. PhoSigNet was designed to store and display human phosphorylation-mediated signal transduction networks, with additional information related to cancer. It contains 11 976 experimentally validated directed edges and 216 871 phosphorylation sites. Moreover, 3491 differentially expressed proteins in human cancer from dbDEPC, 18 907 human cancer variation sites from CanProVar, and 388 hyperphosphorylation sites from PhosphoSitePlus were collected as annotation information. Compared with other phosphorylation-related databases, PhoSigNet not only takes the kinase-substrate regulatory relationship pairs into account, but also extends regulatory relationships up- and downstream (e.g., from ligand to receptor, from G protein to kinase, and from transcription factor to targets). Furthermore, PhoSigNet allows the user to investigate the impact of phosphorylation modifications on cancer. By using one set of in-house time series phosphoproteomics data, the reconstruction of a conditional and dynamic phosphorylation-mediated signaling network was exemplified. We expect PhoSigNet to be a useful database and analysis platform benefiting both proteomics and cancer studies.

Role of phosphoproteomics in the development of personalized cancer therapies

Cell signalling pathways driven by protein and lipid kinases contribute to the onset and progression of virtually all cancer types. Consequently, several inhibitors against these enzymes have clinical utility for the treatment of different forms of cancer. A problem that hampers further development is that not all patients respond equally well to kinase inhibitors and a significant proportion of those that initially respond eventually develop resistance. This review considers how an integrative analysis of kinase signalling may be used to address this issue. Advances in the biophysics of mass spectrometry, in biochemical procedures for phosphopeptide enrichment, and in computational approaches for label-free quantification have contributed to the development of phosphoproteomics workflows compatible with the analysis of clinical material. These developments, together with new bioinformatics tools to derive information on signalling circuitry from phosphoproteomics data, allow investigating kinase networks with unprecedented depth. Phosphoproteomics technology is starting to be used in translational research and, with further developments, such methods may also be able to measure the circuitry of cancer signalling networks in routine clinical assays. This review reflects on how this information could be used to accurately predict the best kinase inhibitor for each individual cancer patient.

Phosphotyrosine signaling analysis in human tumors is confounded by systemic ischemia-driven artifacts and intra-specimen heterogeneity

Tumor protein phosphorylation analysis may provide insight into intracellular signaling networks underlying tumor behavior, revealing diagnostic, prognostic or therapeutic information. Human tumors collected by The Cancer Genome Atlas program potentially offer the opportunity to characterize activated networks driving tumor progression, in parallel with the genetic and transcriptional landscape already documented for these tumors. However, a critical question is whether cellular signaling networks can be reliably analyzed in surgical specimens, where freezing delays and spatial sampling disparities may potentially obscure physiologic signaling. To quantify the extent of these effects, we analyzed the stability of phosphotyrosine (pTyr) sites in ovarian and colon tumors collected under conditions of controlled ischemia and in the context of defined intratumoral sampling. Cold-ischemia produced a rapid, unpredictable, and widespread impact on tumor pTyr networks within 5 minutes of resection, altering up to 50% of pTyr sites by more than 2-fold. Effects on adhesion and migration, inflammatory response, proliferation, and stress response pathways were recapitulated in both ovarian and colon tumors. In addition, sampling of spatially distinct colon tumor biopsies revealed pTyr differences as dramatic as those associated with ischemic times, despite uniform protein expression profiles. Moreover, intratumoral spatial heterogeneity and pTyr dynamic response to ischemia varied dramatically between tumors collected from different patients. Overall, these findings reveal unforeseen phosphorylation complexity, thereby increasing the difficulty of extracting physiologically relevant pTyr signaling networks from archived tissue specimens. In light of this data, prospective tumor pTyr analysis will require appropriate sampling and collection protocols to preserve in vivo signaling features.

Augmentation of multiple protein kinase activities associated with secondary imatinib resistance in gastrointestinal stromal tumors as revealed by quantitative phosphoproteome analysis

Mutations in the Kit receptor tyrosine kinase gene (KIT), which result in constitutive activation of the protein (KIT), are causally related to the development of gastrointestinal stromal tumors (GISTs). Imatinib, a targeted anticancer drug, exerts a therapeutic effect against GISTs by repressing the kinase activity of KIT. Long-term administration of this drug, however, causes the emergence of imatinib-resistant GISTs. We performed quantitative phosphoproteome analysis using a cell-based GIST model system comprising an imatinib-sensitive GIST cell line (GIST882), GIST882 under treatment with imatinib (GIST882-IM), and secondary imatinib-resistant GIST882 (GIST882-R). Phosphorylated peptides were purified from each cell line using titania-based affinity chromatography or anti-phosphotyrosine immunoprecipitation, and then subjected to LC-MS/MS based quantitative phosphoproteome analysis. Using this method we identified augmentation of the kinase activities of multiple elements of the signal transduction pathway, especially KIT and EGFR. Although, these elements were up-regulated in GIST882-R, no additionally mutated KIT mRNA was found in secondary imatinib-resistant GIST cells. Treatment of GIST882-R with imatinib in combination with gefitinib, an EGFR inhibitor, partially prevented cell growth, implying that EGFR may be involved in acquisition of secondary imatinib resistance in GIST.

BIOLOGICAL SIGNIFICANCE

In this study, we performed a quantitative phosphoproteome analysis using a cell culture-based GIST model system. The goal of the study was to investigate the mechanism of acquired resistance in GISTs against imatinib, a molecularly targeted drug that inhibits kinase activity of the KIT protein and that has been approved for the treatment of GISTs. In imatinib-resistant GIST cells, we observed elevated expression of KIT and restoration of its kinase activity, as well as activation of multiple proliferative signaling pathways. Our results indicate that the effects of even so-called 'molecularly targeted' drugs, are broad rather than convergent, and that the mechanisms of action of such drugs during continuous administration are extremely complex.

Quantitative phosphoproteomics of Alzheimer's disease reveals cross-talk between kinases and small heat shock proteins

Abnormal phosphorylation contributes to the formation of neurofibrillary tangles in Alzheimer's disease (AD), but may play other signaling roles during AD pathogenesis. In this study, we employed IMAC followed by LC-MS/MS to identify phosphopeptides from eight individual AD and eight age-matched control postmortem human brain tissues. Using this approach, we identified 5569 phosphopeptides in frontal cortex across all 16 cases in which phosphopeptides represented 80% of all peptide spectral counts collected following IMAC enrichment. Marker selection identified 253 significantly altered phosphopeptides by precursor intensity, changed by at least 1.75-fold relative to controls, with an empirical false discovery rate below 7%. Approximately 21% of all significantly altered phosphopeptides in AD tissue were derived from tau. Of the other 142 proteins hyperphosphorylated in AD, membrane, synapse, cell junction, and alternatively spliced proteins were overrepresented. Of these, we validated differential phosphorylation of HSP 27 (HSPB1) and crystallin-alpha-B (CRYAB) as hyperphosphorylated by Western blotting. We further identified a network of phosphorylated kinases, which coenriched with phosphorylated small HSPs. This supports a hypothesis that a number of kinases are regulating and/or regulated by the small HSP folding network.

Cellular behavior as a dynamic field for exploring bone bioengineering: a closer look at cell-biomaterial interface

Bone is a highly dynamic and specialized tissue, capable of regenerating itself spontaneously when afflicted by minor injuries. Nevertheless, when major lesions occur, it becomes necessary to use biomaterials, which are not only able to endure the cellular proliferation and migration, but also to substitute the original tissue or integrate itself to it. With the life expectancy growth, regenerative medicine has been gaining constant attention in the reconstructive field of dentistry and orthopedy. Focusing on broadening the therapeutic possibilities for the regeneration of injured organs, the development of biomaterials allied with the applicability of gene therapy and bone bioengineering has been receiving vast attention over the recent years. The progress of cellular and molecular biology techniques gave way to new-guided therapy possibilities. Supported by multidisciplinary activities, tissue engineering combines the interaction of physicists, chemists, biologists, engineers, biotechnologist, dentists and physicians with common goals: the search for materials that could promote and lead cell activity. A well-oriented combining of scaffolds, promoting factors, cells, together with gene therapy advances may open new avenues to bone healing in the near future. In this review, our target was to write a report bringing overall concepts on tissue bioengineering, with a special attention to decisive biological parameters for the development of biomaterials, as well as to discuss known intracellular signal transduction as a new manner to be explored within this field, aiming to predict in vitro the quality of the host cell/material and thus contributing with the development of regenerative medicine.

Application of molecular technologies for phosphoproteomic analysis of clinical samples

The integration of small kinase inhibitors and monoclonal antibodies into oncological practice has opened a new paradigm for treating cancer patients. As proteins are the direct targets of the new generations of targeted therapeutics, many of which are kinase/enzymatic inhibitors, there is an increasing interest in developing technologies capable of monitoring post-translational changes of the human proteome for the identification of new predictive, prognostic and therapeutic biomarkers. It is well known that the vast majority of the activation/deactivation of these drug targets is driven by phosphorylation. This review provides a description of the main proteomic platforms (planar and bead array, reverse phase protein microarray, phosphoflow, AQUA and mass spectrometry) that have successfully been used for measuring changes in phosphorylation level of drug targets and downstream substrates using clinical specimens. Major emphasis was given to the strengths and weaknesses of the different platforms and to the major barriers that are associated with the analysis of the phosphoproteome. Finally, a number of examples of application of the above-mentioned technologies in the clinical setting are reported.

Network dynamics in the tumor microenvironment

The evolutionary path from tumor initiation to metastasis can only be fully understood by considering cancer cells as part of a multi-species ecosystem within the tumor microenvironment. This paper reviews and suggests two important recent trends. Firstly, I review arguments that interactions among diverse cells in the tumor microenvironment create a distinct cellular environment that can confer growth advantages, resist interventions, and allow tumors to remain dormant for long periods. Second, I review and highlight a trend toward data-rich, molecularly detailed, computational models of the tumor microenvironment. I argue that data-driven molecularly detailed tumor microenvironment models can now be built using data from multiple emerging high-throughput technologies, and that such models can pinpoint mechanisms of dysregulation and suggest specific drug targets and follow up experiments.

System level dynamics of post-translational modifications

Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal-response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase-substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies.

Protein phosphorylation analysis based on proton release detection: potential tools for drug discovery

Phosphorylation is the most important post-translational modification of proteins in eukaryotic cells and it is catalysed by enzymes called kinases. The balance between protein phosphorylation and dephosphorylation is critical for the regulation of physiological processes and its unbalance is the cause of several diseases. Conventional assays used to analyse the kinase activity are limited as they rely heavily on phospho-specific antibodies and radioactive tags. This makes their use impractical for high throughput drug discovery platforms. We have developed two versatile methods to detect the release of protons (H(+)) associated with the protein phosphorylation catalysed by kinases. The first approach is based on the pH-sensitive response of oxide-semiconductor interfaces and the second method detects the pH changes in phosphorylation reaction using a commercial micro-pH electrode. The proposed methods successfully detected phosphorylation of myelin basic protein by PKC-α kinase. These techniques can be readily adopted for multiplexed arrays and high throughput analysis of kinase activity, which will represent an important innovation in biomedical research and drug discovery.

Cost-effective isobaric tagging for quantitative phosphoproteomics using DiART reagents

We describe the use of an isobaric tagging reagent, Deuterium isobaric Amine Reactive Tag (DiART), for quantitative phosphoproteomic experiments. Using DiART tagged custom mixtures of two phosphorylated peptides from alpha casein and their non-phosphorylated counterparts, we demonstrate the compatibility of DiART with TiO2 affinity purification of phosphorylated peptides. Comparison of theoretical vs. experimental reporter ion ratios reveals accurate quantification of phosphorylated peptides over a dynamic range of more than 15-fold. Using DiART labelling and TiO2 enrichment (DiART-TiO2) with large quantities of proteins (8 mg) from the cell lysate of model fungus Aspergillus nidulans, we quantified 744 unique phosphopeptides. Overlap of median values of TiO2 enriched phosphopeptides with theoretical values indicates accurate trends. Altogether these findings confirm the feasibility of performing quantitative phosphoproteomic experiments in a cost-effective manner using isobaric tagging reagents, DiART.

Mutually exclusive acetylation and ubiquitylation among enzymes involved in glucose metabolism

The posttranslational modification (PTM) in protein occurs in a regiospecific manner. In addition, the most commonly occurring PTMs involve similar residues in proteins such as acetylation, ubiquitylation, methylation and sumoylation at the lysine residue and phosphorylation and O-GlcNAc modification at serine/threonine residues. Thus, the possibility of modification sites where two such PTMs may occur in a mutually exclusive manner (ME-PTM) is much higher than known. A recent surge in the identification and the mapping of the commonly occurring PTMs in proteins has revealed that this is indeed the case. However, in what way such ME-PTM sites are regulated and what could be their relevance in the coordinated network of protein function remains to be known. To gain such potential insights in a biological context, we analyzed two most prevalent PTMs on the lysine residue by acetylation and ubiquitylation along with the most abundant PTM in proteins by phosphorylation among enzymes involved in glucose metabolism, a fundamental process in biology. The analysis of the PTM data sets has revealed two important clues that may be intrinsically associated with their regulation and function. First, the most commonly occurring PTMs by phosphorylation, acetylation and ubiquitylation are widespread and clustered in most of the enzymes involved in glucose metabolism; and the prevalence of phosphorylation sites correlates with the number of acetylation and ubiquitylation sites including the ME-modification sites. Second, the prevalence of ME-acetylation/ubiquitylation sites is exceptionally high among enzymes involved in glucose metabolism and have distinct pattern among the subset of enzymes of glucose metabolism such as glycolysis, tricarboxylic acid (TCA) cycle, glycogen synthesis, and the irreversible steps of gluconeogenesis. We hypothesize that phosphorylation including tyrosine phosphorylation plays an important role in the regulation of ME-acetylation/ubiquitylation sites and their similar pattern among the subset of functionally related proteins allows their coordinated regulation in the normal physiology. Similarly their coordinated dysregulation may underlie the disease processes such as reprogrammed metabolism in cancer, obesity, type 2 diabetes, and cardiovascular diseases. Our hypothesis provides an opportunity to understand the regulation of ME-PTMs in proteins and their relevance at the network level and is open for experimental validation.

Novel and cost-effective 6-plex isobaric tagging reagent, DiART, is effective for identification and relative quantification of complex protein mixtures using PQD fragmentation

Deuterium isobaric Amine Reactive Tag (DiART) reagents facilitate relative quantification during proteomic analysis in a functionally similar manner to commercially available isobaric tag for relative and absolute quantitation (iTRAQ) and tandem mass tag (TMT) reagents. In contrast to iTRAQ and TMT, DiART reagents incorporate deuterium isotopes which significantly reduce the number of required synthesis steps and hence have potential to significantly reduce reagent production cost. We examined the capability of DiART for performing quantitative proteomic experiments using a linear ion-trap mass spectrometer with Pulsed Q Dissociation (PQD) fragmentation. Using a synthetic peptide tagged with DiART reagent, we observed a precise mass shift of 144.79 Da on the triply charged precursor ion, which shows complete derivatization of the N-terminus and ε-amino group of lysine. A DiART tagged tryptic digest of bovine serum albumin showed a sequence coverage of 57.99% which was very comparable to that showed by iTRAQ, 54.77%. Furthermore, a ten protein mixture tagged with DiART reagents and mixed in 1:1:1:1:1:1 exhibited < 15% error, whereas a linear trend (slope of 1.085) was observed when tagged proteins were mixed in the ratio 2:1:2:4:10:14 and plotted against theoretical ratios. Finally, when complex cell-wall protein mixtures from the model fungus A. nidulans were tagged with DiART reagents and mixed in different ratios, they exhibited similar trends. We conclude that DiART reagents are capable of performing quantitative proteomic experiments using PQD on a linear ion trap mass spectrometer.

Phosphoproteomics-based network medicine

One of the major tasks of phosphoproteomics is providing potential biomarkers for either diagnosis or drug targets in medical applications. Because most complex diseases are due to the actions of multiple genes/proteins, the identification of complex phospho-signatures containing multiple phosphorylation events within phosphoproteomics-based networks generates more efficient and robust biomarkers than a single, differentially phosphorylated substrate or site. Here, we briefly summarize the current efforts and progress in this newly emerging field of phosphoproteomics-based network medicine by reviewing the computational (re)construction of phosphorylation-mediated signaling networks from unannotated phosphoproteomic data, the discovery of robust network phospho-signatures and the application of these signatures for classifying cancers and predicting drug responses. The challenges as well as the potential advantages are evaluated and discussed. Although the current techniques are at present far from mature, we believe that such a systematic approach as we describe can generate more useful and robust biomarkers for biomedical usage, even at the current stage of development.

Site-specific NMR mapping and time-resolved monitoring of serine and threonine phosphorylation in reconstituted kinase reactions and mammalian cell extracts

We outline NMR protocols for site-specific mapping and time-resolved monitoring of protein phosphorylation reactions using purified kinases and mammalian cell extracts. These approaches are particularly amenable to intrinsically disordered proteins and unfolded, regulatory protein domains. We present examples for the ¹⁵N isotope-labeled N-terminal transactivation domain of human p53, which is either sequentially reacted with recombinant enzymes or directly added to mammalian cell extracts and phosphorylated by endogenous kinases. Phosphorylation reactions with purified enzymes are set up in minutes, whereas NMR samples in cell extracts are prepared within 1 h. Time-resolved NMR measurements are performed over minutes to hours depending on the activities of the probed kinases. Phosphorylation is quantitatively monitored with consecutive 2D ¹H-¹⁵N band-selective optimized-flip-angle short-transient (SOFAST)-heteronuclear multiple-quantum (HMQC) NMR experiments, which provide atomic-resolution insights into the phosphorylation levels of individual substrate residues and time-dependent changes thereof, thereby offering unique advantages over western blotting and mass spectrometry.

Proteomic strategies to characterize signaling pathways

Cells respond to external stimuli by transducing signals through a series of intracellular molecules and eliciting an appropriate response. The cascade of events through which the signals are transduced include post-translational modifications such as phosphorylation and ubiquitylation in addition to formation of multi-protein complexes. Improvements in biological mass spectrometry and protein/peptide microarray technology have tremendously improved our ability to probe proteins, protein complexes, and signaling pathways in a high-throughput fashion. Today, a single mass spectrometry-based investigation of a signaling pathway has the potential to uncover the large majority of known signaling intermediates painstakingly characterized over decades in addition to discovering a number of novel ones. Here, we discuss various proteomic strategies to characterize signaling pathways and provide protocols for phosphoproteomic analysis.

Mathematical modelling of the MAP kinase pathway using proteomic datasets

The advances in proteomics technologies offer an unprecedented opportunity and valuable resources to understand how living organisms execute necessary functions at systems levels. However, little work has been done up to date to utilize the highly accurate spatio-temporal dynamic proteome data generated by phosphoprotemics for mathematical modeling of complex cell signaling pathways. This work proposed a novel computational framework to develop mathematical models based on proteomic datasets. Using the MAP kinase pathway as the test system, we developed a mathematical model including the cytosolic and nuclear subsystems; and applied the genetic algorithm to infer unknown model parameters. Robustness property of the mathematical model was used as a criterion to select the appropriate rate constants from the estimated candidates. Quantitative information regarding the absolute protein concentrations was used to refine the mathematical model. We have demonstrated that the incorporation of more experimental data could significantly enhance both the simulation accuracy and robustness property of the proposed model. In addition, we used the MAP kinase pathway inhibited by phosphatases with different concentrations to predict the signal output influenced by different cellular conditions. Our predictions are in good agreement with the experimental observations when the MAP kinase pathway was inhibited by phosphatase PP2A and MKP3. The successful application of the proposed modeling framework to the MAP kinase pathway suggests that our method is very promising for developing accurate mathematical models and yielding insights into the regulatory mechanisms of complex cell signaling pathways.

Beyond 'furballs' and 'dumpling soups' - towards a molecular architecture of signaling complexes and networks

The molecular architectures of intracellular signaling networks are largely unknown. Understanding their design principles and mechanisms of processing information is essential to grasp the molecular basis of virtually all biological processes. This is particularly challenging for human pathologies like cancers, as essentially each tumor is a unique disease with vastly deranged signaling networks. However, even in normal cells we know almost nothing. A few 'signalosomes', like the COP9 and the TCR signaling complexes have been described, but detailed structural information on their architectures is largely lacking. Similarly, many growth factor receptors, for example EGF receptor, insulin receptor and c-Met, signal via huge protein complexes built on large platform proteins (Gab, Irs/Dok, p130Cas[BCAR1], Frs families etc.), which are structurally not well understood. Subsequent higher order processing events remain even more enigmatic. We discuss here methods that can be employed to study signaling architectures, and the importance of too often neglected features like macromolecular crowding, intrinsic disorder in proteins and the sophisticated cellular infrastructures, which need to be carefully considered in order to develop a more mature understanding of cellular signal processing.