Phosphoproteomics-based network medicine

Protein phosphorylation: A potential target in glioma development

Glioma is one of the most common primary brain tumors, and mortality due to this disease is second only to cardiovascular and cerebrovascular diseases. In traditional surgery, it is difficult to eradicate glioma; often recurrence increases its malignant degree, leading to a large number of patients killed by this disease. It is one of the most important subjects to study its pathogenesis and explore effective treatment methods. Research on glioma mechanisms mainly focuses on the effect of DNA methylation in epigenetics. Although there are many studies on protein phosphorylation, there is no overall regulatory mechanism. Protein phosphorylation regulates a variety of cell functions, such as cell growth, division and differentiation, and apoptosis. As a consequence, protein phosphorylation plays a leading part in various activities of glioma, and can also be used as a target to regulate the development of glioma. This review is aimed at studying the effect of protein phosphorylation on glioma, understanding the pathological mechanism, and an in-depth analysis of it. The following is a discussion on glioma growth, migration and invasion, resistance and death in phosphorylation, and the possibility of treating glioma by phosphorylation.

Emerging trends in developing biosensor techniques to undertake plant phosphoproteomic analysis

Protein modifications particularly phosphorylation is governed by a complex array of mechanisms to attain a functional conformation and regulate important biological processes in organisms during external environmental stimuli and hormone signaling. Phosphoproteomics is a promising field of proteomics for identification of proteins with phosphate groups and their impact on structure, function and localization of proteins. Techniques that allow quantitative detection of proteins and their post-translational modifications (PTMs) have immensely led to understand the structural and functional dynamics of proteins. Biosensor systems are a relatively new biotechnological approach that works on the principle of transforming the interactions of different biological samples viz proteins, enzymes, aptamers, nucleic acids and so on into the signals such as electrochemical, colorimetric, optical or magnetic which have been effectively useful in the detection and characterization of phosphoproteins. The focus of our review is to provide a comprehensive account of the critical role and utility of novel biosensors such as, fluorescence based, enrichment based, nanobody based biosensors, as promising technical intercessions to identify phosphoproteins and their influence on structural dynamics of proteins. Furthermore, by studying the innovative phosphoprotein biosensors we will be able to identify the aberrant phosphorylation patterns to precisely diagnose diseases.

Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance

FLT3 mutations are the most frequently identified genetic alterations in acute myeloid leukemia (AML) and are associated with poor clinical outcome, relapse and chemotherapeutic resistance. Elucidating the molecular mechanisms underlying FLT3-dependent pathogenesis and drug resistance is a crucial goal of biomedical research. Given the complexity and intricacy of protein signaling networks, deciphering the molecular basis of FLT3-driven drug resistance requires a systems approach. Here we discuss how the recent advances in mass spectrometry (MS)-based (phospho) proteomics and multiparametric analysis accompanied by emerging computational approaches offer a platform to obtain and systematically analyze cell-specific signaling networks and to identify new potential therapeutic targets.

The crucial role of protein phosphorylation in cell signaling and its use as targeted therapy (Review)

Protein phosphorylation is an important cellular regulatory mechanism as many enzymes and receptors are activated/deactivated by phosphorylation and dephosphorylation events, by means of kinases and phosphatases. In particular, the protein kinases are responsible for cellular transduction signaling and their hyperactivity, malfunction or overexpression can be found in several diseases, mostly tumors. Therefore, it is evident that the use of kinase inhibitors can be valuable for the treatment of cancer. In this review, we discuss the mechanism of action of phosphorylation, with particular attention to the importance of phosphorylation under physiological and pathological conditions. We also discuss the possibility of using kinase inhibitors in the treatment of tumors.

Targeted In-Depth Quantification of Signaling Using Label-Free Mass Spectrometry

Protein phosphorylation encodes information on the activity of kinase-driven signaling pathways that regulate cell biology. This chapter discusses an approach, named TIQUAS (targeted in-depth quantification of signaling), to quantify cell signaling comprehensively and without bias. The workflow-based on mass spectrometry (MS) and computational science-consists of targeting the analysis of phosphopeptides previously identified by shotgun liquid chromatography tandem MS (LC-MS/MS) across the samples that are being compared. TIQUAS therefore takes advantage of concepts derived from both targeted (data-independent) and data-dependent acquisition methods; phosphorylation sites are quantified in all experimental samples regardless of whether or not these phosphopeptides were identified by MS/MS in all runs. As a result, datasets are obtained containing quantitative information on several thousand phosphorylation sites in as many samples and replicates as required in the experimental design, and these rich datasets are devoid of a significant number of missing data points. This chapter discussed the biochemical, analytical, and computational procedures required to apply the approach and for obtaining a biological interpretation of the data in the context of our understanding of cell signaling regulation and kinase-substrate relationships.

Phosphoproteomics to Characterize Host Response During Influenza A Virus Infection of Human Macrophages

Influenza A viruses cause infections in the human respiratory tract and give rise to annual seasonal outbreaks, as well as more rarely dreaded pandemics. Influenza A viruses become quickly resistant to the virus-directed antiviral treatments, which are the current main treatment options. A promising alternative approach is to target host cell factors that are exploited by influenza viruses. To this end, we characterized the phosphoproteome of influenza A virus infected primary human macrophages to elucidate the intracellular signaling pathways and critical host factors activated upon influenza infection. We identified 1675 phosphoproteins, 4004 phosphopeptides and 4146 nonredundant phosphosites. The phosphorylation of 1113 proteins (66%) was regulated upon infection, highlighting the importance of such global phosphoproteomic profiling in primary cells. Notably, 285 of the identified phosphorylation sites have not been previously described in publicly available phosphorylation databases, despite many published large-scale phosphoproteome studies using human and mouse cell lines. Systematic bioinformatics analysis of the phosphoproteome data indicated that the phosphorylation of proteins involved in the ubiquitin/proteasome pathway (such as TRIM22 and TRIM25) and antiviral responses (such as MAVS) changed in infected macrophages. Proteins known to play roles in small GTPase-, mitogen-activated protein kinase-, and cyclin-dependent kinase- signaling were also regulated by phosphorylation upon infection. In particular, the influenza infection had a major influence on the phosphorylation profiles of a large number of cyclin-dependent kinase substrates. Functional studies using cyclin-dependent kinase inhibitors showed that the cyclin-dependent kinase activity is required for efficient viral replication and for activation of the host antiviral responses. In addition, we show that cyclin-dependent kinase inhibitors protect IAV-infected mice from death. In conclusion, we provide the first comprehensive phosphoproteome characterization of influenza A virus infection in primary human macrophages, and provide evidence that cyclin-dependent kinases represent potential therapeutic targets for more effective treatment of influenza infections.

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.

Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data

Cell signaling underlies transcription/epigenetic control of a vast majority of cell-fate decisions. A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. In a typical phosphoproteomics study, phosphorylation sites (substrates) of active kinases are quantified proteome-wide. By analyzing the activities of phosphorylation sites over a time-course, the temporal dynamics of signaling cascades can be elucidated. Since many substrates of a given kinase have similar temporal kinetics, clustering phosphorylation sites into distinctive clusters can facilitate identification of their respective kinases. Here we present a knowledge-based CLUster Evaluation (CLUE) approach for identifying the most informative partitioning of a given temporal phosphoproteomics data. Our approach utilizes prior knowledge, annotated kinase-substrate relationships mined from literature and curated databases, to first generate biologically meaningful partitioning of the phosphorylation sites and then determine key kinases associated with each cluster. We demonstrate the utility of the proposed approach on two time-series phosphoproteomics datasets and identify key kinases associated with human embryonic stem cell differentiation and insulin signaling pathway. The proposed approach will be a valuable resource in the identification and characterizing of signaling networks from phosphoproteomics data.

A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. Mass spectrometry-based technologies have emerged as a powerful tool to profile proteome-wide phosphorylation events in vivo at a single amino acid resolution with high precision. However, development of algorithms to analyze and identify signaling events from high-throughput phosphoproteomics data is still in its infancy. Here we propose a knowledge-based CLUster Evaluation (CLUE) approach for identifying key signaling cascades from time-series phosphoproteomics data. Our approach utilizes known kinase-substrate annotations from curated phosphoproteomics databases to first determine the optimal clustering of the phosphorylation sites and then identify enriched kinase(s). We apply CLUE on time-series phosphoproteomics datasets and identify key kinases associated with human embryonic stem cell differentiation and insulin signaling pathway.

Large-scale label-free phosphoproteomics: from technology to data interpretation

Protein phosphorylation plays a central role in the dynamic intracellular signaling and the control of biochemical pathways in all living cells. Recent advances in high-performance MS/MS-based technology make the large-scale identification and quantification of phosphorylation sites possible. Here, we review the full data generation pipeline, starting from sample preparation methods and LC-MS detection procedures, through to data processing and analysis software tools that facilitate the systematic comparative profiling of thousands of phosphoproteins in different biological specimens in a single experiment. We emphasize current challenges and promising avenues for the mechanistic interpretation and visualization of global phosphorylation networks and their relevance to human health and disease.

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.

dbPPT: a comprehensive database of protein phosphorylation in plants

As one of the most important protein post-translational modifications, the reversible phosphorylation is critical for plants in regulating a variety of biological processes such as cellular metabolism, signal transduction and responses to environmental stress. Numerous efforts especially large-scale phosphoproteome profiling studies have been contributed to dissect the phosphorylation signaling in various plants, while a large number of phosphorylation events were identified. To provide an integrated data resource for further investigations, here we present a comprehensive database of dbPPT (database of Phosphorylation site in PlanTs, at http://dbppt.biocuckoo.org), which contains experimentally identified phosphorylation sites in proteins from plants. The phosphorylation sites in dbPPT were manually curated from the literatures, whereas datasets in other public databases were also integrated. In total, there were 82 175 phosphorylation sites in 31 012 proteins from 20 plant organisms in dbPPT, presenting a larger quantity of phosphorylation sites and a higher coverage of plant species in comparison with other databases. The proportions of residue types including serine, threonine and tyrosine were 77.99, 17.81 and 4.20%, respectively. All the phosphoproteins and phosphorylation sites in the database were critically annotated. Since the phosphorylation signaling in plants attracted great attention recently, such a comprehensive resource of plant protein phosphorylation can be useful for the research community.

Database URL:http://dbppt.biocuckoo.org

Systematic analysis of the phosphoproteome and kinase-substrate networks in the mouse testis

Spermatogenesis is a complex process closely associated with the phosphorylation-orchestrated cell cycle. Elucidating the phosphorylation-based regulations should advance our understanding of the underlying molecular mechanisms. Here we present an integrative study of phosphorylation events in the testis. Large-scale phosphoproteome profiling in the adult mouse testis identified 17,829 phosphorylation sites in 3955 phosphoproteins. Although only approximately half of the phosphorylation sites enriched by IMAC were also captured by TiO2, both the phosphoprotein data sets identified by the two methods significantly enriched the functional annotation of spermatogenesis. Thus, the phosphoproteome profiled in this study is a highly useful snapshot of the phosphorylation events in spermatogenesis. To further understand phosphoregulation in the testis, the site-specific kinase-substrate relations were computationally predicted for reconstructing kinase-substrate phosphorylation networks. A core sub-kinase-substrate phosphorylation networks among the spermatogenesis-related proteins was retrieved and analyzed to explore the phosphoregulation during spermatogenesis. Moreover, network-based analyses demonstrated that a number of protein kinases such as MAPKs, CDK2, and CDC2 with statistically more site-specific kinase-substrate relations might have significantly higher activities and play an essential role in spermatogenesis, and the predictions were consistent with previous studies on the regulatory roles of these kinases. In particular, the analyses proposed that the activities of POLO-like kinases (PLKs) might be dramatically higher, while the prediction was experimentally validated by detecting and comparing the phosphorylation levels of pT210, an indicator of PLK1 activation, in testis and other tissues. Further experiments showed that the inhibition of POLO-like kinases decreases cell proliferation by inducing G2/M cell cycle arrest. Taken together, this systematic study provides a global landscape of phosphoregulation in the testis, and should prove to be of value in future studies of spermatogenesis.

Integrating phosphoproteomics in systems biology

Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS)-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.

CPLM: a database of protein lysine modifications

We reported an integrated database of Compendium of Protein Lysine Modifications (CPLM; http://cplm.biocuckoo.org) for protein lysine modifications (PLMs), which occur at active ε-amino groups of specific lysine residues in proteins and are critical for orchestrating various biological processes. The CPLM database was updated from our previously developed database of Compendium of Protein Lysine Acetylation (CPLA), which contained 7151 lysine acetylation sites in 3311 proteins. Here, we manually collected experimentally identified substrates and sites for 12 types of PLMs, including acetylation, ubiquitination, sumoylation, methylation, butyrylation, crotonylation, glycation, malonylation, phosphoglycerylation, propionylation, succinylation and pupylation. In total, the CPLM database contained 203,972 modification events on 189,919 modified lysines in 45,748 proteins for 122 species. With the dataset, we totally identified 76 types of co-occurrences of various PLMs on the same lysine residues, and the most abundant PLM crosstalk is between acetylation and ubiquitination. Up to 53.5% of acetylation and 33.1% of ubiquitination events co-occur at 10 746 lysine sites. Thus, the various PLM crosstalks suggested that a considerable proportion of lysines were competitively and dynamically regulated in a complicated manner. Taken together, the CPLM database can serve as a useful resource for further research of PLMs.