PAK2 is an effector of TSC1/2 signaling independent of mTOR and a potential therapeutic target for Tuberous Sclerosis Complex

Tuberous sclerosis complex (TSC) is caused by inactivating mutations in either TSC1 or TSC2 and is characterized by uncontrolled mTORC1 activation. Drugs that reduce mTOR activity are only partially successful in the treatment of TSC, suggesting that mTOR-independent pathways play a role in disease development. Here, kinome profiles of wild-type and Tsc2-/- mouse embryonic fibroblasts (MEFs) were generated, revealing a prominent role for PAK2 in signal transduction downstream of TSC1/2. Further investigation showed that the effect of the TSC1/2 complex on PAK2 is mediated through RHEB, but is independent of mTOR and p21RAC. We also demonstrated that PAK2 over-activation is likely responsible for the migratory and cell cycle abnormalities observed in Tsc2-/- MEFs. Finally, we detected high levels of PAK2 activation in giant cells in the brains of TSC patients. These results show that PAK2 is a direct effector of TSC1-TSC2-RHEB signaling and a new target for rational drug therapy in TSC

Mathematical modeling of signaling pathways in osteoarthritis

Purpose: Cartilage homeostasis relies on an intricate balance between anabolic and catabolic processes. In osteoarthritis this balance is shifted towards catabolism, leading to hypertrophy and a gradual degradation of cartilage tissue. So far, drug-based intervention in this process has shown limited progress. We propose to construct a mathematical model of the molecular network that governs key processes in articular cartilage homeostasis. This model can be used as a platform for model expansion by introduction of new experimental findings and hypotheses.\ud \ud Methods: We recently developed ANIMO (Analysis of Networks with Interactive Modeling), an intuitive software tool for modeling molecular networks. Here, we demonstrate a mathematical model of growth plate cartilage using a combination of literature and experimental data. We show how ANIMO allows for intuitive exploration of the model, despite the size and complexity of the model.\ud \ud Results: We constructed a network model of regulatory processes in growth plate chondrocytes. In this model the effects downstream of extracellular growth factors FGF, WNT, IGF-1, PTHrP, Ihh, BMP, and TGF-β are integrated into a cellular response. In silico experiments predict the phenotypic outcome for different inputs and starting states of the model.\ud \ud Osteoarthritic chondrocytes and hypertrophic growth plate chondrocytes show strong parallels in their gene expression profile. We have examined the gene expression profiles of growth plate and articular cartilage. In articular cartilage the expression of the WNT and BMP antagonists DKK1, FRZB and GREM1 is over 10-500 fold higher than in growth plate cartilage. This leads us to think that DKK1, FRZB, GREM1 could act as gatekeepers for preventing hypertrophy. We are currently investigating the range of conditions under which these proteins exert their stabilizing effect on the articular cartilage phenotype in the model. Furthermore, we are interrogating the model to obtain in silico leads to targets for novel combination therapies. Such therapies could be used to intervene in the osteoarthritic state of the network and restore the balanced situation of healthy cartilage.\ud \ud Conclusions: Traditionally, modeling efforts in the realm of molecular cell biology have been the exclusive domain of researchers with a thorough training in mathematics or computer science. We show here that a complex model that is intuitively amenable to exploration and adaptation by biologists is an invaluable asset in cartilage research. Expansion of an existing model with DKK1, FRZB and GREM1 provided evidence for their role in preserving the articular cartilage phenotype

ECHO, the executable CHOndrocyte:A computational model to study articular chondrocytes in health and disease

Computational modeling can be used to investigate complex signaling networks in biology. However, most modeling tools are not suitable for molecular cell biologists with little background in mathematics. We have built a visual-based modeling tool for the investigation of dynamic networks. Here, we describe the development of computational models of cartilage development and osteoarthritis, in which a panel of relevant signaling pathways are integrated. In silico experiments give insight in the role of each of the pathway components and reveal which perturbations may deregulate the basal healthy state of cells and tissues. We used a previously developed computational modeling tool Analysis of Networks with Interactive Modeling (ANIMO) to generate an activity network integrating 7 signal transduction pathways resulting in a network containing over 50 nodes and 200 interactions. We performed in silico experiments to characterize molecular mechanisms of cell fate decisions. The model was used to mimic biological scenarios during cell differentiation using RNA-sequencing data of a variety of stem cell sources as input. In a case-study, we wet-lab-tested the model-derived hypothesis that expression of DKK1 (Dickkopf-1) and FRZB (Frizzled related protein, WNT antagonists) and GREM1 (gremlin 1, BMP antagonist) prevents IL1β (Interleukin 1 beta)-induced MMP (matrix metalloproteinase) expression, thereby preventing cartilage degeneration, at least in the short term. We found that a combination of DKK1, FRZB and GREM1 may play a role in modulating the effects of IL1β induced inflammation in human primary chondrocytes

Application of kinomic array analysis to screen for altered kinases in atrial fibrillation remodeling

BACKGROUND Dysregulation of protein kinase-mediated signaling is an early event in many diseases, including the most common clinical cardiac arrhythmia, atrial fibrillation (AF). Kinomic profiling represents a promising technique to identify candidate kinases. OBJECTIVE In this study we used kinomic profiling to identify kinases altered in AF remodeling using atrial tissue from a canine model of AF (atrial tachypacing). METHODS Left atrial tissue obtained in a previous canine study was used for kinomic array (containing 1024 kinase pseudosubstrates) analysis. Three groups of dogs were included: nonpaced controls and atrial tachypaced dogs, which were contrasted with geranylgeranylacetone-treated dogs with AF, which are protected from AF promotion, to enhance specificity of detection of putative kinases. RESULTS While tachypacing changed activity of 50 kinases, 40 of these were prevented by geranylgeranylacetone and involved in differentiation and proliferation (SRC), contraction, metabolism, immunity, development, cell cycle (CDK4), and survival (Akt). Inhibitors of Akt (MK2206) and CDK4 (PD0332991) and overexpression of a dominant-negative CDK4 phosphorylation mutant protected against tachypacing-induced contractile dysfunction in HL-1 cardiomyocytes. Moreover, patients with AF show down- and upregulation of SRC and Akt phosphorylation, respectively, similar to findings of the kinome array. CONCLUSION Contrasting kinomic array analyses of controls and treated subjects offer a versatile tool to identify kinases altered in atrial remodeling owing to tachypacing, which include Akt, CDK4, and SRC. Ultimately, pharmacological targeting of altered kinases may offer novel therapeutic possibilities to treat clinical AF