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.     

Computational methods for analysis of cellular functions and pathways collectively targeted by differentially expressed microRNA.

This report presents computational methods of analysis of cellular processes, functions, and pathways affected by differentially expressed microRNA, a statistical basis of the gene enrichment analysis method, a modification of enrichment analysis method accounting for combinatorial targeting of Gene Ontology categories by multiple miRNAs and examples of the global functional profiling of predicted targets of differentially expressed miRNAs in cancer. We have also summarized an application of Ingenuity Pathway Analysis tools for in depth analysis of microRNA target sets that may be useful for the biological interpretation of microRNA profiling data. To illustrate the utility of these methods, we report the main results of our recent computational analysis of five published datasets of aberrantly expressed microRNAs in five human cancers (pancreatic cancer, breast cancer, colon cancer, lung cancer, and lymphoma). Using a combinatorial target prediction algorithm and statistical enrichment analysis, we have determined Gene Ontology categories as well as biological functions, disease categories, toxicological categories, and signaling pathways that are: targeted by multiple microRNAs; statistically significantly enriched with target genes; and known to be affected in specific cancers. Our recent computational analysis of predicted targets of co-expressed miRNAs in five human cancers suggests that co-expressed miRNAs provide systemic compensatory response to the abnormal phenotypic changes in cancer cells by targeting a broad range of functional categories and signaling pathways reportedly affected in a particular cancer.     

A perspective for biomedical data integration: Design of databases for flow cytometry

Background

Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level.

Results

To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise.

Conclusion

The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data.     

The representation of heart development in the gene ontology

An understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling.In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject.The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area.     

Joint learning of gene functions--a Bayesian network model approach

In this paper, we develop a machine learning system for determining gene functions from heterogeneous data sources using a Weighted Naive Bayesian network (WNB). The knowledge of gene functions is crucial for understanding many fundamental biological mechanisms such as regulatory pathways, cell cycles and diseases. Our major goal is to accurately infer functions of putative genes or Open Reading Frames (ORFs) from existing databases using computational methods. However, this task is intrinsically difficult since the underlying biological processes represent complex interactions of multiple entities. Therefore, many functional links would be missing when only one or two sources of data are used in the prediction. Our hypothesis is that integrating evidence from multiple and complementary sources could significantly improve the prediction accuracy. In this paper, our experimental results not only suggest that the above hypothesis is valid, but also provide guidelines for using the WNB system for data collection, training and predictions. The combined training data sets contain information from gene annotations, gene expressions, clustering outputs, keyword annotations, and sequence homology from public databases. The current system is trained and tested on the genes of budding yeast Saccharomyces cerevisiae. Our WNB model can also be used to analyze the contribution of each source of information toward the prediction performance through the weight training process. The contribution analysis could potentially lead to significant scientific discovery by facilitating the interpretation and understanding of the complex relationships between biological entities.     

LRRK2 signaling pathways: the key to unlocking neurodegeneration?

Mutations in PARK8, encoding leucine-rich repeat kinase 2 (LRRK2), are a major cause of Parkinson's disease. We contrast data suggesting that changes in LRRK2 activity cause alterations in mitogen-activated protein kinase, translational control, tumor necrosis factor α/Fas ligand and Wnt signaling pathways with the cell biological functions of LRRK2 such as vesicle trafficking. Despite scarce in vivo data on cell signaling, involvement in diverse cell biological functions suggests a role for LRRK2 as an upstream regulator in events leading to neurodegeneration. To stimulate discussion and give direction for future research, we further suggest that despite the importance of the catalytic activity for cytotoxicity, the main cellular function of LRRK2 is linked to assembly of signaling complexes.     

Functional roles for myosin 1c in cellular signaling pathways

Cellular signaling pathways underlie the transfer of information throughout the cell and to adjoining cells and so govern most critical cellular functions. Increasing evidence points to the molecular motor myosin 1c as a prominent player in many signaling cascades, from the integrin-dependent signaling involved in cell migration to the signaling events underlying insulin resistance. Myosin 1c functions on these pathways both via an important role in regulating lipid raft recycling and also via direct involvement in signaling cascades. This review provides an overview of the functional involvement of myosin 1c in cellular signaling and discusses the possible potential for myosin 1c as a target for drug-based treatments for human diseases.     

Identification of pathway deregulation - gene expression based analysis of consistent signal transduction

Signaling pathways belong to a complex system of communication that governs cellular processes. They represent signal transduction from an extracellular stimulus via a receptor to intracellular mediators, as well as intracellular interactions. Perturbations in signaling cascade often lead to detrimental changes in cell function and cause many diseases, including cancer. Identification of deregulated pathways may advance the understanding of complex diseases and lead to improvement of therapeutic strategies. We propose Analysis of Consistent Signal Transduction (ACST), a novel method for analysis of signaling pathways. Our method incorporates information regarding pathway topology, as well as data on the position of every gene in each pathway. To preserve gene-gene interactions we use a subject-sampling permutation model to assess the significance of pathway perturbations. We applied our approach to nine independent datasets of global gene expression profiling. The results of ACST, as well as three other methods used to analyze signaling pathways, are presented in the context of biological significance and repeatability among similar, yet independent, datasets. We demonstrate the usefulness of using information of pathway structure as well as genes' functions in the analysis of signaling pathways. We also show that ACST leads to biologically meaningful results and high repeatability.     

Lipid metabolism modulation by the P2X7 receptor in the immune system and during the course of infection: new insights into the old view

For decades, scientists have described numerous protein pathways and functions. Much of a protein’s function depends on its interactions with different partners, and those partners can change depending on the cell type or system. The P2X7 receptor (P2X7R) is one such multifunctional protein that is related to multiple partners and signaling pathways. The relationship between P2X7R and different enzymes involved in lipid metabolism represents a relatively new field in P2X7R research. This field of research began in epithelial cells and currently includes immune and nervous cells. The P2X7R-lipid metabolism pathway is related to many biological functions of P2X7R, such as cell death and pathogen clearance, and this signaling pathway may be involved in many functions that are dependent on bioactive lipids. In the present review, we will attempt to summarize data related to the P2X7R-lipid metabolism pathway, focusing on signaling pathways and their biological relevance to the immune system and infection.     

Analysis and comparison of metabolic pathway databases

Enormous amounts of data result from genome sequencing projects and new experimental methods. Within this tremendous amount of genomic data 30-40 per cent of the genes being identified in an organism remain unknown in terms of their biological function. As a consequence of this lack of information the overall schema of all the biological functions occurring in a specific organism cannot be properly represented. To understand the functional properties of the genomic data more experimental data must be collected. A pathway database is an effort to handle the current knowledge of biochemical pathways and in addition can be used for interpretation of sequence data. Some of the existing pathway databases can be interpreted as detailed functional annotations of genomes because they are tightly integrated with genomic information. However, experimental data are often lacking in these databases. This paper summarises a list of pathway databases and some of their corresponding biological databases, and also focuses on information about the content and the structure of these databases, the organisation of the data and the reliability of stored information from a biological point of view. Moreover, information about the representation of the pathway data and tools to work with the data are given. Advantages and disadvantages of the analysed databases are pointed out, and an overview to biological scientists on how to use these pathway databases is given.     

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.     

Engineering the recruitment of phosphotyrosine binding domain-containing adaptor proteins reveals distinct roles for RET receptor-mediated cell survival

The RET receptor tyrosine kinase is important for several different biological functions during development. The recruitment at the phosphorylated Tyr(1062) site in RET of a number of different phosphotyrosine binding (PTB) domain-containing adaptor proteins, including Shc and Frs2, plays a dominant role for the multiple different biological functions of the RET receptor during development, including stimulation of cell survival. Here, we demonstrate that a competitive recruitment of Shc as opposed to Frs2 mediates the survival signaling arising from RET activation. Based on results from a peptide array, we have genetically engineered the PTB domain binding site of RET to rewire its recruitment of the PTB proteins Shc and Frs2. An engineered RET that has a competitive interaction with Shc at the expense of Frs2, but not a RET receptor that only recruits Frs2, activates cell survival signaling pathways and is protective from cell death in neuronal SK-N-MC cells. Thus, cell type-specific functions involve a competitive recruitment of different PTB adaptor molecules by RET that activate selective signaling pathways.     

RNA-binding proteins in pluripotency,differentiation, and reprogramming

Embryonic stem cell maintenance, differentiation, and somatic cell reprogramming require the interplay of multiple pluripotency factors, epigenetic remodelers, and extracellular signaling pathways. RNA-binding proteins （RBPs） are involved in a wide range of regulatory pathways, from RNA metabolism to epigenetic modifications. In recent years we have witnessed more and more studies on the discovery of new RBPs and the assessment of their functions in a variety of biological systems, including stem cells. We review the current studies on RBPs and focus on those that have functional implications in pluripotency, differentiation, and/or reprogramming in both the human and mouse systems.     

Revealing signaling pathway deregulation by using gene expression signatures and regulatory motif analysis

Gene expression signatures consisting of tens to hundreds of genes have been found to be informative for different biological states. Recently, many computational methods have been proposed for biological interpretation of such signatures. However, there is a lack of methods for identifying cell signaling pathways whose deregulation results in an observed expression signature. We present a strategy for identifying such signaling pathways and evaluate the strategy using six human and mouse gene expression signatures.     

Uncovering signal transduction networks from high-throughput data by integer linear programming

Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.     

Development of public toxicogenomics software for microarray data management and analysis

A robust bioinformatics capability is widely acknowledged as central to realizing the promises of toxicogenomics. Successful application of toxicogenomic approaches, such as DNA microarray, inextricably relies on appropriate data management, the ability to extract knowledge from massive amounts of data and the availability of functional information for data interpretation. At the FDA's National Center for Toxicological Research (NCTR), we are developing a public microarray data management and analysis software, called ArrayTrack. ArrayTrack is Minimum Information About a Microarray Experiment (MIAME) supportive for storing both microarray data and experiment parameters associated with a toxicogenomics study. A quality control mechanism is implemented to assure the fidelity of entered expression data. ArrayTrack also provides a rich collection of functional information about genes, proteins and pathways drawn from various public biological databases for facilitating data interpretation. In addition, several data analysis and visualization tools are available with ArrayTrack, and more tools will be available in the next released version. Importantly, gene expression data, functional information and analysis methods are fully integrated so that the data analysis and interpretation process is simplified and enhanced. ArrayTrack is publicly available online and the prospective user can also request a local installation version by contacting the authors.     

Pathways database system: an integrated system for biological pathways

MOTIVATION: During the next phase of the Human Genome Project, research will focus on functional studies of attributing functions to genes, their regulatory elements, and other DNA sequences. To facilitate the use of genomic information in such studies, a new modeling perspective is needed to examine and study genome sequences in the context of many kinds of biological information. Pathways are the logical format for modeling and presenting such information in a manner that is familiar to biological researchers. RESULTS: In this paper we present an integrated system, called Pathways Database System, with a set of software tools for modeling, storing, analyzing, visualizing, and querying biological pathways data at different levels of genetic, molecular, biochemical and organismal detail. The novel features of the system include: (a) genomic information integrated with other biological data and presented from a pathway, rather than from the DNA sequence, perspective; (b) design for biologists who are possibly unfamiliar with genomics, but whose research is essential for annotating gene and genome sequences with biological functions; (c) database design, implementation and graphical tools which enable users to visualize pathways data in multiple abstraction levels, and to pose predetermined queries; and (d) an implementation that allows for web(XML)-based dissemination of query outputs (i.e. pathways data) to researchers in the community, giving them control on the use of pathways data. AVAILABILITY: Available on request from the authors.     

On how CCN6 suppresses breast cancer growth and invasion

Living cells communicate with their microenvironment and exchange information through signaling pathways in order to carry out most biological processes. The CCN family of proteins has the ability to coordinate the extracellular and intracellular signaling pathways and epithelial-stromal cross-talks. CCN proteins have been shown to play roles in multiple processes including cancer, either as tumor suppressors or oncogenes. Particularly, loss of CCN6 expression has been reported in highly aggressive breast cancer types, especially in inflammatory breast cancer and breast cancer with axillary lymph node metastasis. Recent findings can better explain the biological relevance of CCN6 as a tumor suppressor protein in breast tumorigenesis. CCN6 loss triggers the process of epithelial to mesenchymal transition (EMT), which converts epithelial cells into migratory and invasive mesenchymal-like cells at least in part through modulation of IGF-1 receptor signaling pathway. Emerging data support the hypothesis that CCN6 also exerts growth factor independent functions, especially related to cell survival and anoikis resistance. Thus, our work provides new insights into the functions and mechanisms of tumor suppression exerted by CCN6 in the breast.