Analytical strategies for shotgun phosphoproteomics: Status and prospects

New analytical strategies for phosphoproteomics, both experimental and computational, have been rapidly introduced in recent years, leading to novel biological findings on the role of protein phosphorylation, which have in turn stimulated further development of the analytical techniques. In this review, we describe the development of analytical strategies for LC–MS/MS-based phosphoproteomics, focusing particularly on recent progress in phosphopeptide enrichment, LC–MS/MS measurement and the subsequent computational analysis. High-coverage analysis of the phosphoproteome has largely been achieved by combining pre-fractionation methods with multiple phosphopeptide enrichment approaches, at some cost in LC–MS/MS measurement time and increased sample loss. Key points for the future will be to further increase the selectivity and the recovery of enrichment methods to achieve higher sensitivity and efficiency in LC–MS/MS analysis in order to detect protein phosphorylation comprehensively, including low-abundance proteins. This is expected to lead to a more detailed understanding of the mechanisms and interactions of phosphorylation-mediated regulatory pathways in biological systems.     

Phosphoproteomics, oncogenic signaling and cancer research

The past 5 years have seen an explosion of phosphoproteomics methods development. In this review, using epidermal growth-factor signaling as a model, we will discuss how phosphoproteomics, along with bioinformatics and computational modeling, have impacted key aspects of oncogenic signaling such as in the temporal fine mapping of phosphorylation events, and the identification of novel tyrosine kinase substrates and phosphorylation sites. We submit that the next decade will see considerable exploitation of phosphoproteomics in cancer research. Such a phenomenon is already happening as exemplified by its use in promoting the understanding of the molecular etiology of cancer and target-directed therapeutics.     

系统生物学——生命科学的新领域

系统生物学是继基因组学、蛋白质组学之后一门新兴的生物学交叉学科,代表21世纪生物学的未来.最近,系统生物学研究机构纷纷成立.在研究上,了解一个复杂的生物系统需要整合实验和计算方法.基因组学和蛋白质组学中的高通量方法为系统生物学发展提供了大量的数据.计算生物学通过数据处理、模型构建和理论分析,成为系统生物学发展的一个必不可缺、强有力的工具.在应用上,系统生物学代表新一代医药开发和疾病防治的方向.     

Phosphoproteomics toolbox: computational biology, protein chemistry and mass spectrometry

Protein phosphorylation is important for regulation of most biological functions and up to 50% of all proteins are thought to be modified by protein kinases. Increased knowledge about potential phosphorylation of a protein may increase our understanding of the molecular processes in which it takes part. Despite the importance of protein phosphorylation, identification of phosphoproteins and localization of phosphorylation sites is still a major challenge in proteomics. However, high-throughput methods for identification of phosphoproteins are being developed, in particular within the fields of bioinformatics and mass spectrometry. In this review, we present a toolbox of current technology applied in phosphoproteomics including computational prediction, chemical approaches and mass spectrometry-based analysis, and propose an integrated strategy for experimental phosphoproteomics.     

Recent developments in mass spectrometry-based quantitative phosphoproteomics.

Protein phosphorylation is a reversible post-translational modification that is involved in virtually all eukaryotic cellular processes and has been studied in great detail in recent years. Many developments in mass spectrometry (MS)-based proteomics have been successfully applied to study protein phosphorylation in highly complicated samples. Furthermore, the emergence of a variety of enrichment strategies has allowed some of the challenges associated with low phosphorylation stoichiometry and phosphopeptide copy number to be overcome. The dynamic nature of protein phosphorylation complicates its analysis; however, a number of methods have been developed to successfully quantitate phosphorylation changes in a variety of cellular systems. The following review details some of the most recent breakthroughs in the study of protein phosphorylation, or phosphoproteomics, using MS-based approaches. The majority of the focus is placed on detailing strategies that are currently used to conduct MS-based quantitative phosphoproteomics.     

Quantitative analysis of cell signaling and drug action via mass spectrometry‐based systems level phosphoproteomics

Protein phosphorylation is a primary form of information transfer in cell signaling pathways and plays a crucial role in regulating biological responses. Aberrant phosphorylation has been implicated in a number of diseases, and kinases and phosphatases, the cellular enzymes that control dynamic phosphorylation events, present attractive therapeutic targets. However, the innate complexity of signaling networks has presented many challenges to therapeutic target selection and successful drug development. Approaches in phosphoproteomics can contribute functional, systems‐level datasets across signaling networks that can provide insight into suitable drug targets, more broadly profile compound activities, and identify key biomarkers to assess clinical outcomes. Advances in MS‐based phosphoproteomics efforts now provide the ability to quantitate phosphorylation with throughput and sensitivity to sample a significant portion of the phosphoproteome in clinically relevant systems. This review will discuss recent work and examples of application data that demonstrate the utility of MS, with a particular focus on the use of quantitative phosphoproteomics and phosphotyrosine‐directed signaling analyses to provide robust measurement for functional biological interpretation of drug action on signaling and phenotypic outcomes.     

Proteomic analysis of cellular signaling

Protein phosphorylation events are key regulators of cellular signaling processes. In the era of functional genomics, rational drug design programs demand large-scale high-throughput analysis of signal transduction cascades. Significant improvements in the area of mass spectrometry-based proteomics have provided exciting opportunities for rapid progress toward global protein phosphorylation analysis. This review summarizes several recent advances made in the field of phosphoproteomics with an emphasis placed on mass spectrometry instrumentation, enrichment methods and quantification strategies. In the near future, these technologies will provide a tool that can be used for quantitative investigation of signal transduction pathways to generate new insights into biologic systems.     

Quantitative phosphoproteomics to characterize signaling networks

Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments in phosphoproteomics technology that have facilitated the application of phosphoproteomics to signaling networks and introduce examples of recent system-wide applications of quantitative phosphoproteomics. Despite the great advances in phosphoproteomics technology there are still several outstanding issues and we provide here our outlook on the current limitations and challenges in the field.     

Phosphoproteomics as a tool to unravel plant regulatory mechanisms

Reversible phosphorylation of proteins plays a key role in many regulatory processes that lie at the basis of life. With plants, much research has focused on protein kinases that are involved in the adaptation to different stress conditions, such as pathogen attack and cold. However, the substrates of these kinases are mostly unknown. With the recent advances in phosphoproteomic techniques, the large-scale identification of kinase substrates, including their phosphorylation sites, is finally possible. Studies in mainly non-plant systems have demonstrated the high potential of this method by uncovering numerous novel phosphorylation events. In this minireview, we focus on recent developments in the field of phosphoproteomics that are based on phosphopeptide isolation from complex mixtures by immobilized metal-affinity chromatography coupled to sequence identification by mass spectrometry. Combination of these methods with labelling techniques now allows quantitative analysis of phosphorylation between different samples. We discuss the potential of this technology to uncover entire phosphoproteomes and signalling pathways in plants in the future.     

Proteomic analysis of cellular signaling

Protein phosphorylation events are key regulators of cellular signaling processes. In the era of functional genomics, rational drug design programs demand large-scale high-throughput analysis of signal transduction cascades. Significant improvements in the area of mass spectrometry-based proteomics have provided exciting opportunities for rapid progress toward global protein phosphorylation analysis. This review summarizes several recent advances made in the field of phosphoproteomics with an emphasis placed on mass spectrometry instrumentation, enrichment methods and quantification strategies. In the near future, these technologies will provide a tool that can be used for quantitative investigation of signal transduction pathways to generate new insights into biologic systems.     

Towards functional phosphoproteomics by mapping differential phosphorylation events in signaling networks

Protein phosphorylation plays a central role in many signal transduction pathways that mediate biological processes. Novel quantitative mass spectrometry-based methods have recently revealed phosphorylation dynamics in animals, yeast, and plants. These methods are important for our understanding of how differential phosphorylation participates in translating distinct signals into proper physiological responses, and shifted research towards screening for potential cancer therapies and in-depth analysis of phosphoproteomes. In this review, we aim to describe current progress in quantitative phosphoproteomics. This emerging field has changed numerous static pathways into dynamic signaling networks, and revealed protein kinase networks that underlie adaptation to environmental stimuli. Mass spectrometry enables high-throughput and high-quality analysis of differential phosphorylation at a site-specific level. Although determination of differential phosphorylation between treatments is analogous to detecting differential gene expression, the large body of statistical techniques that has been developed for analysis of differential gene expression is not generally applied for detecting differential phosphorylation. We suggest possible improvements for analysis of quantitative phosphorylation by increasing the number of biological replicates and adapting statistical tests used for gene expression profiling and widely implemented in freely available software tools.     

Improved understanding of gene expression regulation using systems biology

This article reviews the current state of systems biology approaches, including the experimental tools used to generate ‘omic’ data and computational frameworks to interpret this data. Through illustrative examples, systems biology approaches to understand gene expression and gene expression regulation are discussed. Some of the challenges facing this field and the future opportunities in the systems biology era are highlighted.     

Proteomic analysis of phosphorylation in cancer

Constitutive activity of kinases is known to be crucial for a tumor to maintain its malignant phenotype, a phenomenon which is often referred to as oncogene addiction. The in-depth analysis of aberrant signaling pathways by the analysis of protein phosphorylation has become feasible through recent advances in proteomics technology. In this article we will review developments in the field of phosphoproteomics and its application in cancer research. The most widely used technologies for the generic enrichment of phosphopeptides are discussed as well as targeted approaches for the analysis of a specific subset of phosphopeptides. Validation experiments of phosphorylation sites using targeted mass spectrometry are also explained. Finally, we will highlight applications of phosphoproteomic technology in cancer research using cell lines and tissue.     

Advances in the analysis of protein phosphorylation

Phosphorylation is one of the most relevant and ubiquitous post-translational modifications. Despite its relevance, the analysis of protein phosphorylation has been revealed as one of the most challenging tasks due to its highly dynamic nature and low stoichiometry. However, the development and introduction of new analytical methods are modifying rapidly and substantially this field. Especially important has been the introduction of more sensitive and specific methods for phosphoprotein and phosphopeptide purification as well as the use of more sensitive and accurate MS-based analytical methods. The integration of both approaches has enabled large-scale phosphoproteome studies to be performed, an unimaginable task few years ago. Additionally, methods originally developed for differential proteomics have been adapted making the study of the highly dynamic nature of protein phosphorylation feasible. This review aims at offering an overview on the most frequently used methods in phosphoprotein and phosphopeptide enrichment as well as on the most recent MS-based analysis strategies. Current strategies for quantitative phosphoproteomics and the study of the dynamics of protein phosphorylation are highlighted.     

Directional and quantitative phosphorylation networks.

Directionality in protein signalling networks is due to modulated protein-protein interactions and is fundamental for proper signal progression and response to external and internal cues. This property is in part enabled by linear motifs embedding post-translational modification sites. These serve as recognition sites, guiding phosphorylation by kinases and subsequent binding of modular domains (e.g. SH2 and BRCT). Characterization of such modification-modulated interactions on a proteome-wide scale requires extensive computational and experimental analysis. Here, we review the latest advances in methods for unravelling phosphorylation-mediated cellular interaction networks. In particular, we will discuss how the combination of new quantitative mass-spectrometric technologies and computational algorithms together are enhancing mapping of these largely uncharted dynamic networks. By combining quantitative measurements of phosphorylation events with computational approaches, we argue that systems level models will help to decipher complex diseases through the ability to predict cellular systems trajectories.     

The current state of the art of quantitative phosphoproteomics and its applications to diabetes research

Protein phosphorylation is a fundamental regulatory mechanism in many cellular processes and aberrant perturbation of phosphorylation has been implicated in various human diseases. Kinases and their cognate inhibitors have been considered as hotspots for drug development. Therefore, the emerging tools, which enable a system-wide quantitative profiling of phosphoproteome, would offer a powerful impetus in unveiling novel signaling pathways, drug targets and/or biomarkers for diseases of interest. This review highlights recent advances in phosphoproteomics, the current state of the art of the technologies and the challenges and future perspectives of this research area. Finally, some exemplary applications of phosphoproteomics in diabetes research are underscored.     

Artificial intelligence approaches to human-microbiome protein–protein interactions

Host-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review recent advancements in computational methods to predict microbial effects on human cells with a special focus on protein–protein interactions. We categorize recent methods from traditional ones to more recent deep learning methods, followed by several challenges and potential solutions in structure-based approaches. This review serves as a brief guide to the current status and future directions in the field.     

Metabolomics and its role in understanding cellular responses in plants

A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics. This special review article is dedicated to the commemoration of the retirement of Dr. Oluf L. Gamborg after 25 years of service as Founding Managing Editor of Plant Cell Reports. RB and KN have contributed equally to this review.