Cellular signaling in Abdominal Aortic Aneurysm

Abdominal aortic aneurysms (AAAs) are highly lethal cardiovascular diseases without effective medications. However, the molecular and signaling mechanisms remain unclear. A series of pathological cellular processes have been shown to contribute to AAA formation, including vascular extracellular matrix remodeling, inflammatory and immune responses, oxidative stress, and dysfunction of vascular smooth muscle cells. Each cellular process involves complex cellular signaling, such as NF-κB, MAPK, TGFβ, Notch and inflammasome signaling. In this review, we discuss how cellular signaling networks function in various cellular processes during the pathogenesis and progression of AAA. Understanding the interaction of cellular signaling networks with AAA pathogenesis as well as the crosstalk of different signaling pathways is essential for the development of novel therapeutic approaches to and personalized treatments of AAA diseases.     

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.     

Dynamic analysis of integrated signaling, metabolic, and regulatory networks

Extracellular cues affect signaling, metabolic, and regulatory processes to elicit cellular responses. Although intracellular signaling, metabolic, and regulatory networks are highly integrated, previous analyses have largely focused on independent processes (e.g., metabolism) without considering the interplay that exists among them. However, there is evidence that many diseases arise from multifunctional components with roles throughout signaling, metabolic, and regulatory networks. Therefore, in this study, we propose a flux balance analysis (FBA)–based strategy, referred to as integrated dynamic FBA (idFBA), that dynamically simulates cellular phenotypes arising from integrated networks. The idFBA framework requires an integrated stoichiometric reconstruction of signaling, metabolic, and regulatory processes. It assumes quasi-steady-state conditions for “fast” reactions and incorporates “slow” reactions into the stoichiometric formalism in a time-delayed manner. To assess the efficacy of idFBA, we developed a prototypic integrated system comprising signaling, metabolic, and regulatory processes with network features characteristic of actual systems and incorporating kinetic parameters based on typical time scales observed in literature. idFBA was applied to the prototypic system, which was evaluated for different environments and gene regulatory rules. In addition, we applied the idFBA framework in a similar manner to a representative module of the single-cell eukaryotic organism Saccharomyces cerevisiae. Ultimately, idFBA facilitated quantitative, dynamic analysis of systemic effects of extracellular cues on cellular phenotypes and generated comparable time-course predictions when contrasted with an equivalent kinetic model. Since idFBA solves a linear programming problem and does not require an exhaustive list of detailed kinetic parameters, it may be efficiently scaled to integrated intracellular systems that incorporate signaling, metabolic, and regulatory processes at the genome scale, such as the S. cerevisiae system presented here.     

Viruses associated with human cancer

It is estimated that viral infections contribute to 15-20% of all human cancers. As obligatory intracellular parasites, viruses encode proteins that reprogram host cellular signaling pathways that control proliferation, differentiation, cell death, genomic integrity, and recognition by the immune system. These cellular processes are governed by complex and redundant regulatory networks and are surveyed by sentinel mechanisms that ensure that aberrant cells are removed from the proliferative pool. Given that the genome size of a virus is highly restricted to ensure packaging within an infectious structure, viruses must target cellular regulatory nodes with limited redundancy and need to inactivate surveillance mechanisms that would normally recognize and extinguish such abnormal cells. In many cases, key proteins in these same regulatory networks are subject to mutation in non-virally associated diseases and cancers. Oncogenic viruses have thus served as important experimental models to identify and molecularly investigate such cellular networks. These include the discovery of oncogenes and tumor suppressors, identification of regulatory networks that are critical for maintenance of genomic integrity, and processes that govern immune surveillance.     

In the Beginning,There Was Protein Phosphorylation

The importance of reversible protein phosphorylation to cellular regulation cannot be overstated. In eukaryotic cells, protein kinase/phosphatase signaling pathways regulate a staggering number of cellular processes, including cell proliferation, cell death (apoptosis, necroptosis, necrosis), metabolism (at both the cellular and organismal levels), behavior and neurological function, development, and pathogen resistance. Although protein phosphorylation as a mode of eukaryotic cell regulation is familiar to most biochemists, many are less familiar with protein kinase/phosphatase signaling networks that function in prokaryotes. In this thematic minireview series, we present four minireviews that cover the important field of prokaryotic protein phosphorylation.     

Computational modeling of cellular signaling processes embedded into dynamic spatial contexts

Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.     

Trafficking coordinate description of intracellular transport control of signaling networks

Many cellular networks rely on the regulated transport of their components to transduce extracellular information into precise intracellular signals. The dynamics of these networks is typically described in terms of compartmentalized chemical reactions. There are many important situations, however, in which the properties of the compartments change continuously in a way that cannot naturally be described by chemical reactions. Here, we develop an approach based on transport along a trafficking coordinate to precisely describe these processes and we apply it explicitly to the TGF-β signal transduction network, which plays a fundamental role in many diseases and cellular processes. The results of this newly introduced approach accurately capture the distinct TGF-β signaling dynamics of cells with and without cancerous backgrounds and provide an avenue to predict the effects of chemical perturbations in a way that closely recapitulates the observed cellular behavior.     

Hypothesis generation in signaling networks.

Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.     

Genome-wide analysis of signaling networks regulating fatty acid-induced gene expression and organelle biogenesis

Reversible phosphorylation is the most common posttranslational modification used in the regulation of cellular processes. This study of phosphatases and kinases required for peroxisome biogenesis is the first genome-wide analysis of phosphorylation events controlling organelle biogenesis. We evaluate signaling molecule deletion strains of the yeast Saccharomyces cerevisiae for presence of a green fluorescent protein chimera of peroxisomal thiolase, formation of peroxisomes, and peroxisome functionality. We find that distinct signaling networks involving glucose-mediated gene repression, derepression, oleate-mediated induction, and peroxisome formation promote stages of the biogenesis pathway. Additionally, separate classes of signaling proteins are responsible for the regulation of peroxisome number and size. These signaling networks specify the requirements of early and late events of peroxisome biogenesis. Among the numerous signaling proteins involved, Pho85p is exceptional, with functional involvements in both gene expression and peroxisome formation. Our study represents the first global study of signaling networks regulating the biogenesis of an organelle.     

Cancer proteomics: from signaling networks to tumor markers

Along with the great strides that have been made towards understanding cancer, has come a realization of the complexity of molecular events that lead to malignancy. Proteomics-based approaches, which enable the quantitative investigation of both cellular protein expression levels and protein–protein interactions involved in signaling networks, promise to define the molecules controlling the processes involved in cancer.     

Network medicine

To more effectively target complex diseases like cancer, diabetes and schizophrenia, we may need to rethink our strategies for drug development and the selection of molecular targets for pharmacological treatments. Here, we discuss the potential use of protein signaling networks as the targets for new therapeutic intervention. We argue that by targeting the architecture of aberrant signaling networks associated with cancer and other diseases new therapeutic strategies can be implemented. Transforming medicine into a network driven endeavour will require quantitative measurements of cell signaling processes; we will describe how this may be performed and combined with new algorithms to predict the trajectories taken by a cellular system either in time or through disease states. We term this approach, network medicine.     

Cancer proteomics: from signaling networks to tumor markers

Along with the great strides that have been made towards understanding cancer, has come a realization of the complexity of molecular events that lead to malignancy. Proteomics-based approaches, which enable the quantitative investigation of both cellular protein expression levels and protein–protein interactions involved in signaling networks, promise to define the molecules controlling the processes involved in cancer.     

ATM and ATR: networking cellular responses to DNA damage

Maintenance of genome stability depends on the appropriate response to DNA damage. This response is based on complex networks of signaling pathways that activate numerous processes and lead ultimately to damage repair and cellular survival - or apoptosis. The protein kinases ATM and ATR are master controllers of some of these networks, acting either in concert or separately to orchestrate the responses to specific types of DNA damage or stalled replication. Understanding their mode of action is essential to our understanding of how cells cope with genotoxic stress.     

Phospholipase D in the signaling networks of plant response to abscisic acid and reactive oxygen species

Phospholipase D (PLD) has been implicated in different cellular processes in plant growth, development, and stress responses. Recent results have provided insights into the molecular mechanism by which PLD and its lipid product phosphatidic acid (PA) participate in cell signaling. Effector proteins that have been identified for PLD and PA in plants include a heterotrimeric G protein, protein phosphatase, and protein kinase. Evidence has been presented for a direct link from a PLD, PA, to a target protein in specific physiological processes. PLD and PA play multiple roles in the signaling networks of plant response to abscisic acid and reactive oxygen species.     

Genome-wide analysis of signaling domain function

Approximately 2.5% of human gene products contain one or more small domains that drive interactions between proteins and other cellular components in cell signaling processes. The many interactions driven by these relatively simple domains are thought to cooperate with one another to yield complex signaling networks that allow very fine control of cell function. In principle, if we can understand all domain-mediated interactions it should be possible to model these networks. Genome-wide analysis of signaling domain interactions represents a first step in this direction, and several advances of this sort in yeast have been reported over the past year. These reports suggest, for some domains at least, that the prospect of generating 'wiring diagrams' with this simple approach is feasible.     

The involvement of the interleukin-1 receptor-associated kinases (IRAKs) in cellular signaling networks controlling inflammation

Innate immunity and inflammation plays a key role in host defense and wound healing. However, Excessive or altered inflammatory processes can contribute to severe and diverse human diseases including cardiovascular disease, diabetes and cancer. The interleukin-1 receptor-associated kinases (IRAKs) are critically involved in the regulation of intracellular signaling networks controlling inflammation. Collective studies indicate that IRAKs are present in many cell types, and can mediate signals from various cell receptors including toll-like-receptors (TLRs). Consequently, diverse downstream signaling processes can be elicited following the activation of various IRAKs. Given the critical and complex roles IRAK proteins play, it is not surprising that genetic variations in human IRAK genes have been found to be linked with various human inflammatory diseases. This review intends to summarize the recent advances regarding the regulations of various IRAK proteins and their cellular functions in mediating inflammatory signaling processes.     

Linear Population Allocation by Bistable Switches in Response to Transient Stimulation

Many cellular decision processes, including proliferation, differentiation, and phenotypic switching, are controlled by bistable signaling networks. In response to transient or intermediate input signals, these networks allocate a population fraction to each of two distinct states (e.g. OFF and ON). While extensive studies have been carried out to analyze various bistable networks, they are primarily focused on responses of bistable networks to sustained input signals. In this work, we investigate the response characteristics of bistable networks to transient signals, using both theoretical analysis and numerical simulation. We find that bistable systems exhibit a common property: for input signals with short durations, the fraction of switching cells increases linearly with the signal duration, allowing the population to integrate transient signals to tune its response. We propose that this allocation algorithm can be an optimal response strategy for certain cellular decisions in which excessive switching results in lower population fitness.