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

Toward quantitative phosphotyrosine profiling in vivo

Tyrosine phosphorylation is a dynamic reversible post-translational modification that regulates many aspects of cell biology. To understand how this modification controls biological function, it is necessary to not only identify the specific sites of phosphorylation, but also to quantify how phosphorylation levels on these sites may be altered under specific physiological conditions. Due to its sensitivity and accuracy, mass spectrometry (MS) has widely been applied to the identification and characterization of phosphotyrosine signaling across biological systems. In this review we highlight the advances in both MS and phosphotyrosine enrichment methods that have been developed to enable the identification of low level tyrosine phosphorylation events. Computational and manual approaches to ensure confident identification of phosphopeptide sequence and determination of phosphorylation site localization are discussed along with methods that have been applied to the relative quantification of large numbers of phosphorylation sites. Finally, we provide an overview of the challenges ahead as we extend these technologies to the characterization of tyrosine phosphorylation signaling in vivo. With these latest developments in analytical and computational techniques, it is now possible to derive biological insight from quantitative MS-based analysis of signaling networks in vitro and in vivo. Application of these approaches to a wide variety of biological systems will define how signal transduction regulates cellular physiology in health and disease

Labeling and Identification of Direct Kinase Substrates

Identifying kinase substrates is an important step in mapping signal transduction pathways, but it remains a difficult and time-consuming process. Analog-sensitive (AS) kinases have been used to selectively tag and identify direct kinase substrates in lysates from whole cells. In this approach, a γ-thiol adenosine triphosphate analog and an AS kinase are used to selectively thiophosphorylate target proteins. Thiophosphate is used as a chemical handle to purify peptides from a tryptic digest, and target proteins are identified by liquid chromatography and tandem mass spectrometry (LC-MS/MS). Here, we describe an updated strategy for labeling AS kinase substrates, solid-phase capture of thiophosphorylated peptides, incorporation of stable isotope labeling in cell culture for filtering nonspecific background peptides, enrichment of phosphorylated target peptides to identify low-abundance targets, and analysis by LC-MS/MS

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN[subscript 2] vs immediate flash freezing (iFF) in LN[subscript 2] on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen.James S. McDonnell FoundationUnited States-Israel Binational Science FoundationNational Institutes of Health (U.S.) (Grant U54 CA112967)National Institutes of Health (U.S.) (Grant U24 CA159988

Signaling for death: tyrosine phosphorylation in the response to glucose deprivation

The shift from oxidative phosphorylation to aerobic glycolysis in cancer has focused attention on the altered metabolism of cancer cells as a means of therapeutic intervention. Metabolic dysregulation in cancer was first proposed by Warburg in the 1930s, and this topic remains an active area of research. While previous studies have explored the connection between cellular signaling and metabolism, many have focused on a small subset of components within a complex network of proteins, enzymes, and biochemical signals. In a recent article published in Molecular Systems Biology, Graham et al (2012) endeavor to better understand the relationship between metabolism and signaling at the network level. Although the question of how cancer cells respond to glucose starvation posited by the authors is relatively simple, the answer ends up being unexpectedly complex. To answer this question, the authors use mass spectrometry and other biochemical profiling techniques to demonstrate a connection between glucose levels, reactive oxygen species (ROS), and alterations in phosphotyrosine-mediated signaling in glioblastoma cell lines

Mcl-1 integrates the opposing actions of signaling pathways that mediate survival and apoptosis

Mcl-1 is a member of the Bcl2-related protein family that is a critical mediator of cell survival. Exposure of cells to stress causes inhibition of Mcl-1 mRNA translation and rapid destruction of Mcl-1 protein by proteasomal degradation mediated by a phosphodegron created by glycogen synthase kinase 3 (GSK3) phosphorylation of Mcl-1. Here we demonstrate that prior phosphorylation of Mcl-1 by the c-Jun N-terminal protein kinase (JNK) is essential for Mcl-1 phosphorylation by GSK3. Stress-induced Mcl-1 degradation therefore requires the coordinated activity of JNK and GSK3. Together, these data establish that Mcl-1 functions as a site of signal integration between the proapoptotic activity of JNK and the prosurvival activity of the AKT pathway that inhibits GSK3

Integrated data management and validation platform for phosphorylated tandem mass spectrometry data

MS/MS is a widely used method for proteome-wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false-positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open-source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho-MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval.National Science Foundation (U.S.). Graduate Research Fellowship Progra

Qualitatively Different T Cell Phenotypic Responses to IL-2 versus IL-15 Are Unified by Identical Dependences on Receptor Signal Strength and Duration

IL-2 and IL-15 are common γ-chain family cytokines involved in regulation of T cell differentiation and homeostasis. Despite signaling through the same receptors, IL-2 and IL-15 have non-redundant roles in T cell biology, both physiologically and at the cellular level. The mechanisms by which IL-2 and IL-15 trigger distinct phenotypes in T cells remain elusive. To elucidate these mechanisms, we performed a quantitative comparison of the phosphotyrosine signaling network and resulting phenotypes triggered by IL-2 and IL-15. This study revealed that the signaling networks activated by IL-2 or IL-15 are highly similar and that T cell proliferation and metabolism are controlled in a quantitatively distinct manner through IL-2/15R signal strength independent of the cytokine identity. Distinct phenotypes associated with IL-2 or IL-15 stimulation therefore arise through differential regulation of IL-2/15R signal strength and duration because of differences in cytokine–receptor binding affinity, receptor expression levels, physiological cytokine levels, and cytokine–receptor intracellular trafficking kinetics. These results provide important insights into the function of other shared cytokine and growth factor receptors, quantitative regulation of cell proliferation and metabolism through signal transduction, and improved design of cytokine based clinical immunomodulatory therapies for cancer and infectious diseases.National Institutes of Health (U.S.) (Grant U54CA11927)National Institutes of Health (U.S.) (Grant R01 AI065824)United States. Army Research Office (Institute for Collaborative Biotechnologies Grant W911NF-09-0001

MARQUIS: A multiplex method for absolute quantification of peptides and posttranslational modifications

Absolute quantification of protein expression and posttranslational modifications by mass spectrometry has been challenging due to a variety of factors, including the potentially large dynamic range of phosphorylation response. To address these issues, we have developed MARQUIS—Multiplex Absolute Regressed Quantification with Internal Standards—a novel mass spectrometry-based approach using a combination of isobaric tags and heavy-labelled standard peptides, to construct internal standard curves for peptides derived from key nodes in signal transduction networks. We applied MARQUIS to quantify phosphorylation dynamics within the ​EGFR network at multiple time points following stimulation with several ligands, enabling a quantitative comparison of ​EGFR phosphorylation sites and demonstrating that receptor phosphorylation is qualitatively similar but quantitatively distinct for each ​EGFR ligand tested. MARQUIS was also applied to quantify the effect of ​EGFR kinase inhibition on glioblastoma patient-derived xenografts. MARQUIS is a versatile method, broadly applicable and extendable to multiple mass spectrometric platforms.United States-Israel Binational Science FoundationNational Institutes of Health (U.S.) (Grant U54 CA112967)National Institutes of Health (U.S.) (Grant R01 CA118705)National Institutes of Health (U.S.) (Grant R01 CA096504)Mayo Brain Tumor SPORE CA10896

A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes

We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biological processes that are associated with thermodynamic-like constraints. The analysis yields a molecular description of a stable steady state that is common across all tumors. It also resolves molecular descriptions of unbalanced processes that are shared by several tumors, such as hyperactivated phosphoprotein signaling networks. Further, it resolves unbalanced processes that provide unique classifiers of tumor subgroups. The results of the theoretical interpretation are compared against those of statistical multivariate methods and are shown to provide a superior level of resolution for identifying unbalanced processes in GBM tumors. The identification of specific constraints for each GBM tumor suggests tumor-specific combination therapies that may reverse this imbalance