Meeting report: Signal transduction meets systems biology

ABSTRACT: In the 21st century, systems-wide analyses of biological processes are getting more and more realistic. Especially for the in depth analysis of signal transduction pathways and networks, various approaches of systems biology are now successfully used. The EU FP7 large integrated project SYBILLA (Systems Biology of T-cell Activation in Health and Disease) coordinates such an endeavor. By using a combination of experimental data sets and computational modelling, the consortium strives for gaining a detailed and mechanistic understanding of signal transduction processes that govern T-cell activation. In order to foster the interaction between systems biologists and experimentally working groups, SYBILLA co-organized the 15th meeting "Signal Transduction: Receptors, Mediators and Genes" together with the Signal Transduction Society (STS). Thus, the annual STS conference, held from November 7 to 9, 2011 in Weimar, Germany, provided an interdisciplinary forum for research on signal transduction with a major focus on systems biology addressing signalling events in T-cells. Here we report on a selection of ongoing projects of SYBILLA and how they were discussed at this interdisciplinary conference.     

Is receptor oligomerization causally linked to activation of the EGF receptor kinase?

Transduction of a signal from an extracellular peptide hormone to produce an intracellular response is often mediated by a cell surface receptor, which is usually a glycoprotein. The secondary intracellular signal(s) generated after hormone binding to the receptor have been intensively studied. The nature of the primary signal generated by ligand binding to the receptor is understood less well in most cases. The particular case of the epidermal growth factor (EGF) receptor is analyzed, and evidence for or against two dissimilar models of primary signal transduction is reviewed. Evidence for the most widely accepted current model is found to be unconvincing. Evidence for the other model is substantial but indirect; a direct test of this model remains to be done.     

The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) σ factor protein family

The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) σ factors – the largest group of alternative σ factors – represent the third fundamental mechanism of bacterial signal transduction, with about six such regulators on average per bacterial genome. Together with their cognate anti-σ factors, they represent a highly modular design that primarily facilitates transmembrane signal transduction. A comprehensive analysis of the ECF σ factor protein family identified more than 40 distinct major groups of ECF σ factors. The functional relevance of this classification is supported by the sequence similarity and domain architecture of cognate anti-σ factors, genomic context conservation, and potential target promoter motifs. Moreover, this phylogenetic analysis revealed unique features indicating novel mechanisms of ECF-mediated signal transduction. This classification, together with the web tool ECF finder and the information stored in the Microbial Signal Transduction (MiST) database, provides a comprehensive resource for the analysis of ECF σ factor-dependent gene regulation.     

Function,diversity, and evolution of signal transduction in prokaryotes

Major areas covered at the Bacterial Locomotion and Signal Transduction (BLAST) meeting included the clustering of chemoreceptors and its significance to signal amplification, organelle biogenesis, motility, developmental responses mediated by "chemotaxis" operons, and advances in two-component signaling mechanisms.     

A tale of two machines: a review of the BLAST meeting,Tucson, AZ, 20–24 January 2013

Since its inception, Bacterial Locomotion and Signal Transduction (BLAST) meetings have been the place to exchange and share the latest developments in the field of bacterial signal transduction and motility. At the 12th BLAST meeting, held last January in Tucson, AZ, researchers from all over the world met to report and discuss progress in diverse aspects of the field. The majority of these advances, however, came at the level of atomic level structures and their associated mechanisms. This was especially true of the biological machines that sense and respond to environmental changes.     

Bacterial moving and shaking: the 11th blast meeting

Since their inception 20 years ago, the biennial blast (Bacterial Locomotion and Signal Transduction) meetings instantly became the place to be for exchanging and sharing the latest developments in the field of bacterial motility and signalling. At the 11th edition, held last January in New Orleans, LA, researchers reported on the myriad of mechanisms involved in bacterial movement, sensing and adaptation, ranging from the molecular level to multicellular behaviour. New insights into bacterial signalling phenomena were gained, revealing previously unsuspected layers of complexity, particularly in mechanisms ensuring signal transduction fidelity and novel links to metabolic processes.     

PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

Background  

A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem.     

Knowledge representation of signal transduction pathways

MOTIVATIONS: Signal transduction is the common term used to define a diverse topic that encompasses a large body of knowledge about the biochemical mechanisms. Since most of the knowledge of signal transduction resides in scientific articles and is represented by texts in natural language or by diagrams, there is the need of a knowledge representation model for signal transduction pathways that can be as readily processed by a computer as it is easily understood by humans. RESULTS: A signal transduction pathway representation model is presented. It is based on a compound graph structure and is designed to handle the diversity and hierarchical structure of pathways. A prototype knowledge base was implemented on a deductive database and a number of biological queries are demonstrated on it.     

Wheat defense genes in fungal (Puccinia striiformis) infection

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is one of the most important diseases of wheat worldwide. To isolate defense-related genes against the pathogen, a suppression subtractive hybridization library was constructed for an incompatible interaction. From the library, 652 sequences were determined to be unigenes, of which 31 were determined as genes involved in signal transduction and 77 were predicted to encode defense-related proteins. Expression patterns of 12 selected signal transduction and defense-related genes were determined using quantitative real-time polymerase chain reaction. Signal transduction genes started increasing their expression at 12 h post inoculation (hpi), and expressions of the most of the transport and resistance-related genes were induced at 18 hpi. The gene expression results indicate specific molecular and cellular activities during the incompatible interaction between wheat and the stripe rust pathogen. In general, the expression increase of wheat signal transduction genes soon after inoculation with the pathogen inducing various defense-related genes, including reactive oxygen species, ATP-binding cassette (ABC) transporters, pathogenesis-related proteins, and genes involved in the phenylpropanoid pathway. The activities of these defense genes work in a sequential and concerted manner to result in a hypersensitive response.     

Proteomic analysis of phosphorylation, oxidation and nitrosylation in signal transduction

Signal transduction pathways control cell fate, survival and function. They are organized as intricate biochemical networks which enable biochemical protein activities, crosstalk and subcellular localization to be integrated and tuned to produce highly specific biological responses in a robust and reproducible manner. Post translational Modifications (PTMs) play major roles in regulating these processes through a wide variety of mechanisms that include changes in protein activities, interactions, and subcellular localizations. Determining and analyzing PTMs poses enormous challenges. Recent progress in mass spectrometry (MS) based proteomics have enhanced our capability to map and identify many PTMs. Here we review the current state of proteomic PTM analysis relevant for signal transduction research, focusing on two areas: phosphorylation, which is well established as a widespread key regulator of signal transduction; and oxidative modifications, which from being primarily viewed as protein damage now start to emerge as important regulatory mechanisms.     

A model for signal transduction in suspension cultures of Taxus chinensis var. mairei induced by an oligosaccharide from Fusarium oxysporum

A non-linear cascade model is proposed to describe the signal transduction pathway in suspension cultures of Taxus chinensis var. mairei induced by an oligosaccharide from Fusarium oxysporum. The oxidative burst intensity, which was defined as the amount of the free radicals including superoxide anion (O² ), H₂O₂ and OH^– and measured by ESR spectrometry, was used as the signal characteristic and the theory of electronic signal transduction cascade was then applied to derive the initial model. The model shows that the signal transduction cascade process is composed of three cascade nets, represented by the phosphorylation of a G-protein, activation of an ion channel and phospholipase C, and phosphorylation of protein kinase C. The three reactions were calculated as beginning at 30.5, 48.8 and 141.4 min after elicitation, and the maximum variation rates of the signal intensity in the three nets occurred at 43.2, 80.6 and 192.6 min, respectively. The validity of the model predictions was verified by experimental data.     

Molecular Mechanisms of Hormonal Activity. II. Kinase Systems. Systems with Intracellular Receptors. Transactivation of STS

Hormone receptors and other components, functional mechanisms, and biological role of analyzed signal transduction systems (STS) are described. The recently revealed module principle of the structure and STS transactivation providing diversity and plasticity of regulation are highlighted. STS activities are significantly changed in many diseases. Novel promising pharmaceuticals targeted to certain components of STS increase in number from year to year. The data published by the beginning of January 2004 are summarized in this review.__________Translated from Biokhimiya, Vol. 70, No. 4, 2005, pp. 476–492.Original Russian Text Copyright © 2005 by Kulinsky, Kolesnichenko.Part I of this review, Molecular Mechanisms of Hormonal Activity. I. Receptors. Neuromediators. Systems with Second Messengers, was published in Biochemistry (Moscow), Vol. 70, No. 1.     

Current Screens Based on the AlphaScreen? Technology for Deciphering Cell Signalling Pathways

Global deciphering of signal transduction pathways represents a new challenge of the post-genomic era. However, for the majority of these signaling pathways the role(s), the function(s) and the interaction(s) of the signaling intermediates remain to be characterized in an integrated fashion. The global molecular study of cell signaling pathways and networks consequently requires sensitive, robust technologies which may allow in addition multi-parallel and highthroughput applications. The Alphascreen™ technology, relying on a bead-based homogenous approach, constitutes a valuable tool to detect and quantify a wide range of signaling events such as enzymatic activities or biomolecular interactions. In this article, we exhaustively review the literature and report the broad spectrum of Alphascreen™-based applications in the study of signal transduction pathways.Key Words: Signal transduction, signaling, Alphascreen™.     

Loss of cilia causes embryonic lung hypoplasia,liver fibrosis,and cholestasis in the talpid3 ciliopathy mutant

Sonic hedgehog plays an essential role in maintaining hepatoblasts in a proliferative non-differentiating state during embryogenesis. Transduction of the Hedgehog signaling pathway is dependent on the presence of functional primary cilia and hepatoblasts, therefore, must require primary cilia for normal function. In congenital syndromes in which cilia are absent or non-functional (ciliopathies) hepatorenal fibrocystic disease is common and primarily characterized by ductal plate malformations which underlie the formation of liver cysts, as well as less commonly, by hepatic fibrosis, although a role for abnormal Hedgehog signal transduction has not been implicated in these phenotypes. We have examined liver, lung and rib development in the talpid³ chicken mutant, a ciliopathy model in which abnormal Hedgehog signaling is well characterized. We find that the talpid³ phenotype closely models that of human short-rib polydactyly syndromes which are caused by the loss of cilia, and exhibit hypoplastic lungs and liver failure. Through an analysis of liver and lung development in the talpid³ chicken, we propose that cilia in the liver are essential for the transduction of Hedgehog signaling during hepatic development. The talpid³ chicken represents a useful resource in furthering our understanding of the pathology of ciliopathies beyond the treatment of thoracic insufficiency as well as generating insights into the role Hedgehog signaling in hepatic development.     

Loss of cilia causes embryonic lung hypoplasia,liver fibrosis,and cholestasis in the talpid3 ciliopathy mutant

Sonic hedgehog plays an essential role in maintaining hepatoblasts in a proliferative non-differentiating state during embryogenesis. Transduction of the Hedgehog signaling pathway is dependent on the presence of functional primary cilia and hepatoblasts, therefore, must require primary cilia for normal function. In congenital syndromes in which cilia are absent or non-functional (ciliopathies) hepatorenal fibrocystic disease is common and primarily characterized by ductal plate malformations which underlie the formation of liver cysts, as well as less commonly, by hepatic fibrosis, although a role for abnormal Hedgehog signal transduction has not been implicated in these phenotypes. We have examined liver, lung and rib development in the talpid³ chicken mutant, a ciliopathy model in which abnormal Hedgehog signaling is well characterized. We find that the talpid³ phenotype closely models that of human short-rib polydactyly syndromes which are caused by the loss of cilia, and exhibit hypoplastic lungs and liver failure. Through an analysis of liver and lung development in the talpid³ chicken, we propose that cilia in the liver are essential for the transduction of Hedgehog signaling during hepatic development. The talpid³ chicken represents a useful resource in furthering our understanding of the pathology of ciliopathies beyond the treatment of thoracic insufficiency as well as generating insights into the role Hedgehog signaling in hepatic development.     

High-frequency transduction of pBR322 by cytosine-substituted T4 bacteriophage: evidence for encapsulation and transfer of head-to-tail plasmid concatemers

Transduction of plasmid pBR322 by cytosine-substituted T4 phages has been studied. Three T4 phage mutants which substitute cytosine for all of hydroxymethylcytosine residues in the DNA, were shown to transduce pBR322 at frequencies of 2 × 10^?2 to 4 × 10^?3 transductants per singly infected cell. Also, three T4 phage strains which partially substitute cytosine for hydroxymethylcytosine, transduced pBR322 at frequencies of 2 × 10^?3 to 2 × 10^?4. The transduction frequencies of pBR322 we attained are at least 10-fold higher than those reported by G. G. Wilson, K. Young, and G. J. Edlin (1979, Nature (London)280, 80–82). We found that multiplicity of infection in preparation of the transducing phage is the most important factor affecting the frequency of pBR322 transduction. When a lysate made at a multiplicity of infection ranging from 0.5 to 0.05 was used as the donor phage, transduction frequency of pBR322 was 10- to 40-fold higher than that of high-m.o.i. lysate. The transduction frequency was not affected by either restriction systems or amber suppressors of the recipient cells. However, no pBR322-containing transductant was obtained when either recA or polA mutants were used as the recipients. DNA from T4dC phage containing pBR322-transducing particles was analyzed on agarose gel electrophoresis after cleavage with restriction endonucleases. It was suggested that the pBR322 DNA in the T4dC phage particles exists as head-to-tail concatemers.     

PESI--an intelligent system for prediction of enzyme-substrate interactions based on experimental constraints

We present a system for predicting protein-protein modifications, and demonstrate its usefulness in the field of signal transduction research. Signal transduction is one of the most important areas of investigation in biological research. One of the major mechanisms frequently employed by cells to regulate signal transduction processes involves protein phosphorylation by various kinases. As many as 1,000 protein kinases and 500 protein phosphatases in the human genome are thought to be involved in phosphorylation processes which regulate all aspects of cell function. The complexity of such interactions stems from the enormous number of factors and interactions, which makes the identification of putative substrates for any given enzyme by straightforward experimentation increasingly difficult. We present here a data mining algorithm, based on the similarity between the modifier proteins and between the modified proteins, and on experimental constraints. The application presented here (PESI) focuses on substrate phosphorylation by various enzymes. This algorithm reduces the number of substrate candidates for experimental study by about two orders of magnitude. Moreover, this algorithm has already yielded predictions for previously unknown substrates of the enzymes PKCdelta and PKCeta, which we have confirmed experimentally.