Background: Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks. Results: We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the dynamic behavior. We have implemented these methods in our software tool CellNetAnalyzer (successor of FluxAnalyzer) and illustrate their applicability using a logical model of T-Cell receptor signaling providing non-intuitive results regarding feedback loops, essential elements, and (logical) signal processing upon different stimuli. Conclusion: The methods and formalisms we propose herein are another step towards the comprehensive functional analysis of cellular interaction networks. Their potential, shown on a realistic T-cell signaling model, makes them a promising tool.

Cold shock proteins are multifunctional RNA/DNA binding proteins, characterized by the presence of one or more cold shock domains. In humans, the best characterized members of this family are denoted Y-box binding proteins, such as Y-box binding protein-1 (YB-1). Biological activities range from the regulation of transcription, splicing and translation, to the orchestration of exosomal RNA content. Indeed, the secretion of YB-1 from cells via exosomes has opened the door to further potent activities. Evidence links a skewed cold shock protein expression pattern with cancer and inflammatory diseases. In this review the evidence for a causative involvement of cold shock proteins in disease development and progression is summarized. Furthermore, the potential application of cold shock proteins for diagnostics and as targets for therapy is elucidated.

The Y-box protein-1 (YB-1) fulfills pleiotropic functions relating to gene transcription, mRNA processing, and translation. It remains elusive how YB-1 shuttling into the nuclear and cytoplasmic compartments is regulated and whether limited proteolysis by the 20S proteasome releases fragments with distinct function(s) and subcellular distribution(s).

Antigenic stimulation of the T cell receptor (TCR) initiates a change from a resting state into an activated one, which ultimately results in proliferation and the acquisition of effector functions. To accomplish this task, T cells require dramatic changes in metabolism. Therefore, we investigated changes of metabolic intermediates indicating for crucial metabolic pathways reflecting the status of T cells. Moreover we analyzed possible regulatory molecules required for the initiation of the metabolic changes. We found that proliferation inducing conditions result in an increase in key glycolytic metabolites, whereas the citric acid cycle remains unaffected. The upregulation of glycolysis led to a strong lactate production, which depends upon AKT/PKB, but not mTOR. The observed upregulation of lactate dehydrogenase results in increased lactate production, which we found to be dependent on IL-2 and to be required for proliferation. Additionally we observed upregulation of Glucose-transporter 1 (GLUT1) and glucose uptake upon stimulation, which were surprisingly not influenced by AKT inhibition. Our findings suggest that AKT plays a central role in upregulating glycolysis via induction of lactate dehydrogenase expression, but has no impact on glucose uptake of T cells. Furthermore, under apoptosis inducing conditions, T cells are not able to upregulate glycolysis and induce lactate production. In addition maintaining high glycolytic rates strongly depends on IL-2 production.

Background: Signaling through the TCR is crucial for the generation of different cellular responses including proliferation, differentiation, and apoptosis. A growing body of evidence indicates that differences in the magnitude and the duration of the signal are critical determinants in eliciting cellular responses.Results: Here, we have analyzed signaling dynamics correlating with either unresponsiveness or proliferation induced upon TCR/CD28 ligation in primary human T cells. We used two widely employed methods to stimulate T cellsin vitro, antibodies either cross-linked in solution (sAbs) or immobilized on microbeads (iAbs). A comparative analysis of the signaling properties of iAbs and sAbs revealed that, under proliferation-inducing conditions, feedback regulation is markedly different from that leading to an unresponsive state. In fact, upon iAbs stimulation TCR-mediated signaling is prolonged by a positive feedback loop involving Erk, whereas sAbs strongly activate inhibitory molecules that likely terminate signaling. We additionally found that, by enhancing the phosphorylation of Src family kinases under proliferation-inducing conditions, signaling and T-cell activation are terminated.Conclusions: In summary, our analysis documents TCR signaling kinetics and feedback regulation under conditions of stimulation inducing either unresponsiveness or proliferation.

T cells orchestrate the adaptive immune response, making them targets for immunotherapy. Although immunosuppressive therapies prevent disease progression, they also leave patients susceptible to opportunistic infections. To identify novel drug targets, we established a logical model describing T-cell receptor (TCR) signaling. However, to have a model that is able to predict new therapeutic approaches, the current drug targets must be included. Therefore, as a next step we generated the interleukin-2 receptor (IL-2R) signaling network and developed a tool to merge logical models. For IL-2R signaling, we show that STAT activation is independent of both Src- and PI3-kinases, while ERK activation depends upon both kinases and additionally requires novel PKCs. In addition, our merged model correctly predicted TCR-induced STAT activation. The combined network also allows information transfer from one receptor to add detail to another, thereby predicting that LAT mediates JNK activation in IL-2R signaling. In summary, the merged model not only enables us to unravel potential cross-talk, but it also suggests new experimental designs and provides a critical step towards designing strategies to reprogram T cells. The cells of the mammalian immune system do not exist in isolation, but rather form an integrated network that is constantly scanning the body for signs of ‘foreign’ invasion. Working together, these cells possess the ability to repel invaders and thereby establish protective immunity. One central population in this network are T lymphocytes; whose role it is to coordinate the activity of the adaptive arm of defense. However, T cells constantly receive multiple inputs and therefore it is not clear how they are able to reach a decision. Traditionally, these inputs are studied in isolation using a top-down or stimulus-response approach. Confounding this issue is that our knowledge of these input pathways is not cell-type-specific, but rather represents the sum of all knowledge related to a given stimulus. Therefore, we have undertaken to validate signaling pathways in primary human T cells. We are particularly interested to study the cross-talk between pathways to see how common elements are utilized to make specific decisions that determine cell fate. In doing so, we have identified new components in what were considered to be well-characterized receptor pathways.