Phosphoproteome Analysis

Protein phosphorylation is directly or indirectly involved in all important cellular events. The understanding of its regulatory role requires the discovery of the proteins involved in these processes and how, where and when protein phosphorylation takes place. Investigation of the phosphoproteome of a cell is becoming feasible today although it still represents a very difficult task especially if quantitative comparisons have to be made. Several different experimental strategies can be employed to explore phosphoproteomes and this review will cover the most important ones such as incorporation of radiolabeled phosphate into proteins, application of specific antibodies against phosphorylated residues and direct staining of phosphorylated proteins in polyacrylamide gels. Moreover, methods to enrich phosphorylated proteins such as affinity chromatography (IMAC) and immunoprecipitation as well as mass spectrometry for identification of phosphorylated peptides and phosphorylation sites are also described.     

Computational Analysis of the Predicted Evolutionary Conservation of Human Phosphorylation Sites

Protein kinase-mediated phosphorylation is among the most important post-translational modifications. However, few phosphorylation sites have been experimentally identified for most species, making it difficult to determine the degree to which phosphorylation sites are conserved. The goal of this study was to use computational methods to characterize the conservation of human phosphorylation sites in a wide variety of eukaryotes. Using experimentally-determined human sites as input, homologous phosphorylation sites were predicted in all 432 eukaryotes for which complete proteomes were available. For each pair of species, we calculated phosphorylation site conservation as the number of phosphorylation sites found in both species divided by the number found in at least one of the two species. A clustering of the species based on this conservation measure was concordant with phylogenies based on traditional genomic measures. For a subset of the 432 species, phosphorylation site conservation was compared to conservation of both protein kinases and proteins in general. Protein kinases exhibited the highest degree of conservation, while general proteins were less conserved and phosphorylation sites were least conserved. Although preliminary, these data tentatively suggest that variation in phosphorylation sites may play a larger role in explaining phenotypic differences among organisms than differences in the complements of protein kinases or general proteins.     

酪氨酸磷酸化蛋白质组学技术研究进展及其在生物医学研究中的应用

在酪氨酸磷酸化蛋白质组学的研究过程中,酪氨酸磷酸化位点的富集是最重要的一步。目前常用的富集方法是抗体亲和富集或SH2 superbinder富集。此外,通过质谱与生物信息学等技术,可实现大规模酪氨酸磷酸化位点的鉴定。对酪氨酸磷酸化蛋白质组学进行深度覆盖研究,揭示癌症发生发展过程中失调的激酶,将有助于深入理解癌症的发生发展过程;且由于75%的致癌基因是酪氨酸激酶基因,酪氨酸激酶抑制剂作为抗癌药物受到了越来越多的关注。应用酪氨酸磷酸化蛋白质组学技术,可以鉴定与癌症等重大疾病相关的酪氨酸激酶,从而帮助找到酪氨酸激酶抑制剂。总之,酪氨酸磷酸化蛋白质组学技术可以在酪氨酸激酶鉴定、酪氨酸激酶抑制剂研究及酪氨酸磷酸化信号通路研究等生物医学领域中得到很好的应用。     

Integrated Quantitative Phosphoproteomics and Cell-Based Functional Screening Reveals Specific Pathological Cardiac Hypertrophy-Related Phosphorylation Sites

Cardiac hypertrophic signaling cascades resulting in heart failure diseases are mediated by protein phosphorylation. Recent developments in mass spectrometry-based phosphoproteomics have led to the identification of thousands of differentially phosphorylated proteins and their phosphorylation sites. However, functional studies of these differentially phosphorylated proteins have not been conducted in a large-scale or high-throughput manner due to a lack of methods capable of revealing the functional relevance of each phosphorylation site. In this study, an integrated approach combining quantitative phosphoproteomics and cell-based functional screening using phosphorylation competition peptides was developed. A pathological cardiac hypertrophy model, junctate-1 transgenic mice and control mice, were analyzed using label-free quantitative phosphoproteomics to identify differentially phosphorylated proteins and sites. A cell-based functional assay system measuring hypertrophic cell growth of neonatal rat ventricle cardiomyocytes (NRVMs) following phenylephrine treatment was applied, and changes in phosphorylation of individual differentially phosphorylated sites were induced by incorporation of phosphorylation competition peptides conjugated with cell-penetrating peptides. Cell-based functional screening against 18 selected phosphorylation sites identified three phosphorylation sites (Ser-98, Ser-179 of Ldb3, and Ser-1146 of palladin) displaying near-complete inhibition of cardiac hypertrophic growth of NRVMs. Changes in phosphorylation levels of Ser-98 and Ser-179 in Ldb3 were further confirmed in NRVMs and other pathological/physiological hypertrophy models, including transverse aortic constriction and swimming models, using site-specific phospho-antibodies. Our integrated approach can be used to identify functionally important phosphorylation sites among differentially phosphorylated sites, and unlike conventional approaches, it is easily applicable for large-scale and/or high-throughput analyses.     

A solid phase extraction-based platform for rapid phosphoproteomic analysis

Protein phosphorylation is among the most common and intensely studied post-translational protein modification. It plays crucial roles in virtually all cellular processes and has been implicated in numerous human diseases, including cancer. Traditional biochemical and genetic methods for identifying and monitoring sites of phosphorylation are laborious and slow and in recent years have largely been replaced by mass spectrometric analysis. Improved methods for phosphopeptide enrichment coupled with faster and more sensitive mass spectrometers have led to an explosion in the size of phosphoproteomic datasets. However, wider application of these methods is limited by equipment costs and the resultant high demand for instrument time as well as by a technology gap between biologists and mass spectrometrists. Here we describe a modified two-step enrichment strategy that employs lysC digestion and step elution from self-packed strong cation exchange (SCX) solid phase extraction (SPE) columns followed by immobilized metal ion affinity chromatography (IMAC) and LC–MS/MS analysis using a hybrid LTQ Orbitrap Velos mass spectrometer. The SCX procedure does not require an HPLC system, demands little expertise, and because multiple samples can be processed in parallel, can provide a large savings of time and labor. We demonstrate this method in conjunction with stable isotope labeling to quantitate peptides harboring >8000 unique phosphorylation sites in yeast in 12 h of instrument analysis time and examine the impact of enzyme choice and instrument platform.     

Prediction of functional phosphorylation sites by incorporating evolutionary information

Protein phosphorylation is a ubiquitous protein post-translational modification, which plays an important role in cellular signaling systems underlying various physiological and pathological processes. Current in silico methods mainly focused on the prediction of phosphorylation sites, but rare methods considered whether a phosphorylation site is functional or not. Since functional phosphorylation sites are more valuable for further experimental research and a proportion of phosphorylation sites have no direct functional effects, the prediction of functional phosphorylation sites is quite necessary for this research area. Previous studies have shown that functional phosphorylation sites are more conserved than non-functional phosphorylation sites in evolution. Thus, in our method, we developed a web server by integrating existing phosphorylation site prediction methods, as well as both absolute and relative evolutionary conservation scores to predict the most likely functional phosphorylation sites. Using our method, we predicted the most likely functional sites of the human, rat and mouse proteomes and built a database for the predicted sites. By the analysis of overall prediction results, we demonstrated that protein phosphorylation plays an important role in all the enriched KEGG pathways. By the analysis of protein-specific prediction results, we demonstrated the usefulness of our method for individual protein studies. Our method would help to characterize the most likely functional phosphorylation sites for further studies in this research area.     

Analysis of phosphorylated proteins and peptides by mass spectrometry

Phosphorylation on serine, threonine and tyrosine residues is an extremely important modulator of protein function. Therefore, there is a great need for methods capable of accurately elucidating sites of phosphorylation. Although full characterization of phosphoproteins remains a formidable analytical challenge, mass spectrometry has emerged as an increasingly viable tool for this task. This review summarizes the methodologies currently available for the analysis of phosphoproteins by mass spectrometry, including enrichment of compounds of interest using immobilized metal affinity chromatography and chemical tagging techniques, detection of phosphopeptides using mass mapping and precursor ion scans, localization of phosphorylation sites by peptide sequencing, and quantitation of phosphorylation by the introduction of mass tags. Despite the variety of powerful analytical methods that are now available, complete characterization of the phosphorylation state of a protein isolated in small quantities from a biological sample remains far from routine.     

Sample preparation and analytical strategies for large-scale phosphoproteomics experiments

Reversible protein phosphorylation is an important post-translational modification that controls a wide range of protein functions including enzyme activity, subcellular localisation, protein degradation, intra- and inter-molecular protein interactions. Significant advances in both phosphopeptide enrichment methods and sensitive mass spectrometry instrumentation have been achieved over the past decade to facilitate the large-scale identification of protein phosphorylation in humans and different animal and microbial model systems. While mass spectrometry provides the ability to identify thousands of phosphorylation sites in a single experiment, the further understanding of the functional significance of this modification on protein substrates requires detailed information on the changes in phosphorylation stoichiometry and protein abundance across experimental paradigms. This review presents different sample preparation methods and analytical strategies used in mass spectrometry-based phosphoproteomics to profile protein phosphorylation and unravel the regulation of this modification on protein function.     

Quantitative phosphoproteomic analysis of signaling network dynamics

Protein phosphorylation mediated cellular signaling is a highly regulated, dynamic process that controls many aspects of cellular biology. Over the past few years many methods have been developed to quantify temporal dynamics of protein phosphorylation, including mass spectrometry, which can be applied in both an unbiased, discovery mode and in a targeted mode to monitor specific phosphorylation sites. Other methods, such as kinase activity assays and antibody microarrays, have been applied to quantify central nodes in the signaling network, yielding intriguing biological insights. This review provides a concise overview of the latest advances in the quantitative analysis of signaling dynamics including a brief commentary on the future of the field.     

Mass Spectrometric Identification of In Vivo Phosphorylation Sites of Differentially Expressed Proteins in Elongating Cotton Fiber Cells

Two-dimensional gel electrophoresis (2-DE)-based proteomics approach was applied to extensively explore the molecular basis of plant development and environmental adaptation. These proteomics analyses revealed thousands of differentially expressed proteins (DEPs) closely related to different biological processes. However, little attention has been paid to how peptide mass fingerprinting (PMF) data generated by the approach can be directly utilized for the determination of protein phosphorylation. Here, we used the software tool FindMod to predict the peptides that might carry the phosphorylation modification by examining their PMF data for mass differences between the empirical and theoretical peptides and then identified phosphorylation sites using MALDI TOF/TOF according to predicted peptide data from these DEP spots in the 2-D gels. As a result, a total of 48 phosphorylation sites of 40 DEPs were successfully identified among 235 known DEPs previously revealed in the 2-D gels of elongating cotton fiber cells. The 40 phosphorylated DEPs, including important enzymes such as enolase, transketolase and UDP-L-rhamnose synthase, are presumed to participate in the functional regulation of numerous metabolic pathways, suggesting the reverse phosphorylation of these proteins might play important roles in elongating cotton fibers. The results also indicated that some different isoforms of the identical DEP revealed in our 2-DE-based proteomics analysis could be annotated by phosphorylation events. Taken together, as the first report of large-scale identification of phosphorylation sites in elongating cotton fiber cells, our study provides not only an excellent example of directly identifying phosphorylation sites from known DEPs on 2-D gels but also provides a valuable resource for future functional studies of phosphorylated proteins in this field.     

A Grammar Inference Approach for Predicting Kinase Specific Phosphorylation Sites

Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.     

Proteomic analysis of in vivo phosphorylated synaptic proteins

In the nervous system, protein phosphorylation is an essential feature of synaptic function. Although protein phosphorylation is known to be important for many synaptic processes and in disease, little is known about global phosphorylation of synaptic proteins. Heterogeneity and low abundance make protein phosphorylation analysis difficult, particularly for mammalian tissue samples. Using a new approach, combining both protein and peptide immobilized metal affinity chromatography and mass spectrometry data acquisition strategies, we have produced the first large scale map of the mouse synapse phosphoproteome. We report over 650 phosphorylation events corresponding to 331 sites (289 have been unambiguously assigned), 92% of which are novel. These represent 79 proteins, half of which are novel phosphoproteins, and include several highly phosphorylated proteins such as MAP1B (33 sites) and Bassoon (30 sites). An additional 149 candidate phosphoproteins were identified by profiling the composition of the protein immobilized metal affinity chromatography enrichment. All major synaptic protein classes were observed, including components of important pre- and postsynaptic complexes as well as low abundance signaling proteins. Bioinformatic and in vitro phosphorylation assays of peptide arrays suggest that a small number of kinases phosphorylate many proteins and that each substrate is phosphorylated by many kinases. These data substantially increase existing knowledge of synapse protein phosphorylation and support a model where the synapse phosphoproteome is functionally organized into a highly interconnected signaling network.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary se-quences can help predict phosphorylation sites catalyzed by different protein kinase and most com-putational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are consid-ered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic de-tection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were ob-tained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and con-venience.     

Prediction of PK-specific phosphorylation site based on information entropy

Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary sequences can help predict phosphorylation sites catalyzed by different protein kinase and most computational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are considered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic detection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were obtained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and convenience.     

Universal and confident phosphorylation site localization using phosphoRS

An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.     

Identification of the phosphorylation sites on intact TRPM7 channels from mammalian cells

Transient receptor potential melastatin 7 (TRPM7) channels are divalent cation-selective ion channels that are permeable to Ca(2+) and Mg(2+). TRPM7 is ubiquitously expressed in vertebrate cells and contains both an ion channel and a kinase domain. TRPM7 plays an important role in regulating cellular homeostatic levels of Ca(2+) and Mg(2+) in mammalian cells. Although studies have shown that the kinase domain of TRPM7 is required for channel activation and can phosphorylate other target proteins, a systematic analysis of intact TRPM7 channel phosphorylation sites expressed in mammalian cells is lacking. We applied mass spectrometric proteomic techniques to identify and characterize the key phosphorylation sites in TRPM7 channels. We identified 14 phosphorylation sites in the cytoplasmic domain of TRPM7, eight of which have not been previously reported. The identification of phosphorylation sites using antibody-based immunopurification and mass spectrometry is an effective approach for defining the phosphorylation status of TRPM7 channels. The present results show that TRPM7 channels are phosphorylated at multiple sites, which serves as a mechanism to modulate the dynamic functions of TRPM7 channels in mammalian cells.     

Multisite Phosphorylation of the Guanine Nucleotide Exchange Factor Cdc24 during Yeast Cell Polarization

Background

Cell polarization is essential for processes such as cell migration and asymmetric cell division. A common regulator of cell polarization in most eukaryotic cells is the conserved Rho GTPase, Cdc42. In budding yeast, Cdc42 is activated by a single guanine nucleotide exchange factor, Cdc24. The mechanistic details of Cdc24 activation at the onset of yeast cell polarization are unclear. Previous studies have suggested an important role for phosphorylation of Cdc24, which may regulate activity or function of the protein, representing a key step in the symmetry breaking process.

Methodology/Principal Findings

Here, we directly ask whether multisite phosphorylation of Cdc24 plays a role in its regulation. We identify through mass spectrometry analysis over thirty putative in vivo phosphorylation sites. We first focus on sites matching consensus sequences for cyclin-dependent and p21-activated kinases, two kinase families that have been previously shown to phosphorylate Cdc24. Through site-directed mutagenesis, yeast genetics, and light and fluorescence microscopy, we show that nonphosphorylatable mutations of these consensus sites do not lead to any detectable consequences on growth rate, morphology, kinetics of polarization, or localization of the mutant protein. We do, however, observe a change in the mobility shift of mutant Cdc24 proteins on SDS-PAGE, suggesting that we have indeed perturbed its phosphorylation. Finally, we show that mutation of all identified phosphorylation sites does not cause observable defects in growth rate or morphology.

Conclusions/Significance

We conclude that lack of phosphorylation on Cdc24 has no overt functional consequences in budding yeast. Yeast cell polarization may be more tightly regulated by inactivation of Cdc42 by GTPase activating proteins or by alternative methods of Cdc24 regulation, such as conformational changes or oligomerization.     

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA in vitro and 13 PKA phosphorylation sites were identified by mass spectrometry. NetPhosK was 100% sensitive and 41% specific in predicting PKA sites in the four proteins. These results demonstrate the potential of using integrated computational and experimental methods for detailed investigations of the phosphoproteome.     

Characterizing the microenvironment surrounding phosphorylated protein sites

Protein phosphorylation plays an important role in various cellular processes. Due to its high complexity, the mechanism needs to be further studied. In the last few years, many methods have been contributed to this field, but almost all of them investigated the mechanism based on protein sequences around protein sites. In this study, we implement an exploration by characterizing the microenvironment surrounding phosphorylated protein sites with a modified shell model, and obtain some significant properties by the rank-sum test, such as the lack of some classes of residues, atoms, and secondary structures. Furthermore, we find that the depletion of some properties affects protein phosphorylation remarkably. Our results suggest that it is a meaningful direction to explore the mechanism of protein phosphorylation from microenvironment and we expect further findings along with the increasing size of phosphorylation and protein structure data.     

Protein scaffolds can enhance the bistability of multisite phosphorylation systems

The phosphorylation of a substrate at multiple sites is a common protein modification that can give rise to important structural and electrostatic changes. Scaffold proteins can enhance protein phosphorylation by facilitating an interaction between a protein kinase enzyme and its target substrate. In this work we consider a simple mathematical model of a scaffold protein and show that under specific conditions, the presence of the scaffold can substantially raise the likelihood that the resulting system will exhibit bistable behavior. This phenomenon is especially pronounced when the enzymatic reactions have sufficiently large K(M), compared to the concentration of the target substrate. We also find for a closely related model that bistable systems tend to have a specific kinetic conformation. Using deficiency theory and other methods, we provide a number of necessary conditions for bistability, such as the presence of multiple phosphorylation sites and the dependence of the scaffold binding/unbinding rates on the number of phosphorylated sites.