Phosphoproteomics strategies for the functional analysis of signal transduction

Protein phosphorylation is a key regulatory mechanism of cellular signalling processes. The analysis of phosphorylated proteins and the characterisation of phosphorylation sites under different biological conditions are some of the most challenging tasks in current proteomics research. Reduction of the sample complexity is one major step for the analysis of low-abundance kinase substrates, which can be achieved by various subcellular fractionation techniques. One strategy is the enrichment of phosphorylated proteins or peptides by immunoprecipitation or chromatography, e.g. immobilised metal affinity chromatography, prior to analysis. 2-DE gels are powerful tools for the analysis of phosphoproteins when combined with new multiplexing techniques like DIGE, phosphospecific stains, autoradiography or immunoblotting. In addition, several gel-free methods combining chromatography with highly sensitive MS have been successfully applied for the analysis of complex phosphoproteomes. Recently developed approaches like KESTREL or 'chemical genetics' and also protein microarrays offer new possibilities for the identification of specific kinase targets. This review summarises various strategies for the analyses of phosphoproteins with a special focus on the identification of novel kinase substrates.     

Integration of conventional quantitative and phospho‐proteomics reveals new elements in activated Jurkat T‐cell receptor pathway maintenance

Recent years have seen a constant development of tools for the global assessment of phosphoproteins. Here, we outline a concept for integrating approaches for quantitative proteomics and phosphoproteomics. The strategy was applied to the analysis of changes in signalling and protein synthesis occurring after activation of the T‐cell receptor (TCR) pathway in a T‐cell line (Jurkat cells). For this purpose, peptides were obtained from four biological replicates of activated and control Jurkat T‐cells and phosphopeptides enriched via a TiO₂‐based chromatographic step. Both phosphopeptide‐enriched and flow‐through fractions were analyzed by LC–MS. We observed 1314 phosphopeptides in the enriched fraction whereas 19 were detected in the flow‐through, enabling the quantification of 414 and eight phosphoproteins in the respective fractions. Pathway analysis revealed the differential regulation of many metabolic pathways. Among the quantified proteins, 11 kinases with known TCR‐related function were detected. A kinase‐substrate database search for the phosphosites identified also confirmed the activity of a further ten kinases. In total, these two approaches provided evidence of 19 unique TCR‐related kinases. The combination of phosphoproteomics and conventional quantitative shotgun analysis leads to a more comprehensive assessment of the signalling networks needed for the maintenance of the activated status of Jurkat T‐cells.     

Quantitative phosphoproteomics strategies for understanding protein kinase-mediated signal transduction pathways

Protein phosphorylation is a central regulatory mechanism of cell signaling pathways. This highly controlled biochemical process is involved in most cellular functions, and defects in protein kinases and phosphatases have been implicated in many diseases, highlighting the importance of understanding phosphorylation-mediated signaling networks. However, phosphorylation is a transient modification, and phosphorylated proteins are often less abundant. Therefore, the large-scale identification and quantification of phosphoproteins and their phosphorylation sites under different conditions are one of the most interesting and challenging tasks in the field of proteomics. Both 2D gel electrophoresis and liquid chromatography-tandem mass spectrometry serve as key phosphoproteomic technologies in combination with prefractionation, such as enrichment of phosphorylated proteins/peptides. Recently, new possibilities for quantitative phosphoproteomic analysis have been offered by technical advances in sample preparation, enrichment, separation, instrumentation, quantification and informatics. In this article, we present an overview of several strategies for quantitative phosphoproteomics and discuss how phosphoproteomic analysis can help to elucidate signaling pathways that regulate various cellular processes.     

Quantitative phosphoproteomics strategies for understanding protein kinase-mediated signal transduction pathways

Protein phosphorylation is a central regulatory mechanism of cell signaling pathways. This highly controlled biochemical process is involved in most cellular functions, and defects in protein kinases and phosphatases have been implicated in many diseases, highlighting the importance of understanding phosphorylation-mediated signaling networks. However, phosphorylation is a transient modification, and phosphorylated proteins are often less abundant. Therefore, the large-scale identification and quantification of phosphoproteins and their phosphorylation sites under different conditions are one of the most interesting and challenging tasks in the field of proteomics. Both 2D gel electrophoresis and liquid chromatography-tandem mass spectrometry serve as key phosphoproteomic technologies in combination with prefractionation, such as enrichment of phosphorylated proteins/peptides. Recently, new possibilities for quantitative phosphoproteomic analysis have been offered by technical advances in sample preparation, enrichment, separation, instrumentation, quantification and informatics. In this article, we present an overview of several strategies for quantitative phosphoproteomics and discuss how phosphoproteomic analysis can help to elucidate signaling pathways that regulate various cellular processes.     

Large-scale identification of novel mitosis-specific phosphoproteins

Systematic identification of phosphoproteins is essential for understanding cellular signalling pathways since phosphorylation plays important roles in cellular regulation. Monoclonal antibody MPM-2 recognizes a discrete set of mitosis-specific phosphoproteins and constitutes a specific tool to investigate the significance of phosphorylation in cell cycle. However, due to the difficulties in identifying antigens revealed on immunoblot membrane, only minority of MPM-2 antigens have been identified. Here we originated proteomics approaches for large-scale identification of MPM-2 phosphoproteins. Mitotic extracts were run on several two-dimensional gel electrophoresis (2D) in parallel, and stained by Coomassie Blue. Each individual spot on one of the gels was excised, and proteins in it were further resolved by regular SDS-electrophoresis and blotted on membrane for MPM-2 stain. Counterparts of the positive proteins were selected on another parallel 2D gel and identified by mass-spectrometry. Using this strategy, 100 spots were excised from Coomassie-stained 2D gel and screened by 1D immunoblots for MPM-2 reactivity, and 22 proteins containing potential MPM-2 epitope were identified in addition to a known MPM-2 antigen, laminin-binding protein. These results were further validated by immunofluorescence, co-immunoprecipitation and in vitro phosphorylation assay. The identification of an unprecedented number of potential MPM-2 phosphoprotein antigens gives new insight into the range of proteins involved in the regulation of the early stages of cell division. Meanwhile, this strategy could be used wherever unknown antigens are explored, especially for antibodies that can recognize more than one antigen.     

Near-infrared fluorescence detection of ATP-biotin-mediated phosphoprotein labeling

Detection of phosphoproteins plays an important role in understanding protein function in cellular signalling pathways. Improved methods for identification and quantification of phosphoproteins are research priorities. Near-infrared (NIR) fluorescence detection of a γ-modified ATP-biotin analog was used to detect protein phosphorylation, using both model kinase substrates and mammalian cell lysates. NIR signal intensity was dependent on substrate and ATP-biotin concentrations.     

Proteomics‐based discovery of biomarkers for paediatric acute lymphoblastic leukaemia: challenges and opportunities

There are important breakthroughs in the treatment of paediatric acute lymphoblastic leukaemia (ALL) since 1950, by which the prognosis of the child majority suffered from ALL has been improved. However, there are urgent needs to have disease‐specific biomarkers to monitor the therapeutic efficacy and predict the patient prognosis. The present study overviewed proteomics‐based research on paediatric ALL to discuss important advances to combat cancer cells and search novel and real protein biomarkers of resistance or sensitivity to drugs which target the signalling networks. We highlighted the importance and significance of a proper phospho‐quantitative design and strategy for paediatric ALL between relapse and remission, when human body fluids from cerebrospinal, peripheral blood, or bone‐marrow were applied. The present article also assessed the schedule for the analysis of body fluids from patients at different states, importance of proteomics‐based tools to discover ALL‐specific and sensitive biomarkers, to stimulate paediatric ALL research via proteomics to ‘build’ the reference map of the signalling networks from leukemic cells at relapse, and to monitor significant clinical therapies for ALL‐relapse.     

Computational models of signalling networks for non-linear control

Artificial signalling networks (ASNs) are a computational approach inspired by the signalling processes inside cells that decode outside environmental information. Using evolutionary algorithms to induce complex behaviours, we show how chaotic dynamics in a conservative dynamical system can be controlled. Such dynamics are of particular interest as they mimic the inherent complexity of non-linear physical systems in the real world. Considering the main biological interpretations of cellular signalling, in which complex behaviours and robust cellular responses emerge from the interaction of multiple pathways, we introduce two ASN representations: a stand-alone ASN and a coupled ASN. In particular we note how sophisticated cellular communication mechanisms can lead to effective controllers, where complicated problems can be divided into smaller and independent tasks.     

Cell-signalling dynamics in time and space

The specificity of cellular responses to receptor stimulation is encoded by the spatial and temporal dynamics of downstream signalling networks. Temporal dynamics are coupled to spatial gradients of signalling activities, which guide pivotal intracellular processes and tightly regulate signal propagation across a cell. Computational models provide insights into the complex relationships between the stimuli and the cellular responses, and reveal the mechanisms that are responsible for signal amplification, noise reduction and generation of discontinuous bistable dynamics or oscillations.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein-protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Reconstruction of cellular signalling networks and analysis of their properties

The study of cellular signalling over the past 20 years and the advent of high-throughput technologies are enabling the reconstruction of large-scale signalling networks. After careful reconstruction of signalling networks, their properties must be described within an integrative framework that accounts for the complexity of the cellular signalling network and that is amenable to quantitative modelling.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein–protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Integrative features of the yeast phosphoproteome and protein-protein interaction map

Following recent advances in high-throughput mass spectrometry (MS)-based proteomics, the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms. Although a critical role of phosphorylation is control of protein signaling, our understanding of the phosphoproteome remains limited. Here, we report unexpected, large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data. First, new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data. This revealed that nearly 60% of ～6,000 yeast genes encode phosphoproteins. We mapped these unified phosphoproteome data on a yeast protein-protein interaction (PPI) network with other yeast multi-omics datasets containing information about proteome abundance, proteome disorders, literature-derived signaling reactomes, and in vitro substratomes of kinases. In the phospho-PPI, phosphoproteins had more interacting partners than nonphosphoproteins, implying that a large fraction of intracellular protein interaction patterns (including those of protein complex formation) is affected by reversible and alternative phosphorylation reactions. Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells, the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level. Moreover, analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells. These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other.