The Enhancer of split and Achaete-Scute complexes of Drosophilids derived from simple ur-complexes preserved in mosquito and honeybee

BACKGROUND: In Drosophila melanogaster the Enhancer of split-Complex [E(spl)-C] consists of seven highly related genes encoding basic helix-loop-helix (bHLH) repressors and intermingled, four genes that belong to the Bearded (Brd) family. Both gene classes are targets of the Notch signalling pathway. The Achaete-Scute-Complex [AS-C] comprises four genes encoding bHLH activators. The question arose how these complexes evolved with regard to gene number in the evolution of insects concentrating on Diptera and the Hymenoptera Apis mellifera. RESULTS: In Drosophilids both gene complexes are highly conserved, spanning roughly 40 million years of evolution. However, in species more diverged like Anopheles or Apis we find dramatic differences. Here, the E(spl)-C consists of one bHLH (mβ) and one Brd family member (mα) in a head to head arrangement. Interestingly in Apis but not in Anopheles, there are two more E(spl) bHLH like genes within 250 kb, which may reflect duplication events in the honeybee that occurred independently of that in Diptera. The AS-C may have arisen from a single sc/l'sc like gene which is well conserved in Apis and Anopheles and a second ase like gene that is highly diverged, however, located within 50 kb. CONCLUSION: E(spl)-C and AS-C presumably evolved by gene duplication to the nowadays complex composition in Drosophilids in order to govern the accurate expression patterns typical for these highly evolved insects. The ancestral ur-complexes, however, consisted most likely of just two genes: E(spl)-C contains one bHLH member of mβ type and one Brd family member of mα type and AS-C contains one sc/l'sc and a highly diverged ase like gene

Modeling system states in liver cells: Survival, apoptosis and their modifications in response to viral infection

<p>Abstract</p> <p>Background</p> <p>The decision pro- or contra apoptosis is complex, involves a number of different inputs, and is central for the homeostasis of an individual cell as well as for the maintenance and regeneration of the complete organism.</p> <p>Results</p> <p>This study centers on Fas ligand (FasL)-mediated apoptosis, and a complex and internally strongly linked network is assembled around the central FasL-mediated apoptosis cascade. Different bioinformatical techniques are employed and different crosstalk possibilities including the integrin pathway are considered. This network is translated into a Boolean network (74 nodes, 108 edges). System stability is dynamically sampled and investigated using the software SQUAD. Testing a number of alternative crosstalk possibilities and networks we find that there are four stable system states, two states comprising cell survival and two states describing apoptosis by the intrinsic and the extrinsic pathways, respectively. The model is validated by comparing it to experimental data from kinetics of cytochrome c release and caspase activation in wildtype and Bid knockout cells grown on different substrates. Pathophysiological modifications such as input from cytomegalovirus proteins M36 and M45 again produces output behavior that well agrees with experimental data.</p> <p>Conclusion</p> <p>A network model for apoptosis and crosstalk in hepatocytes shows four different system states and reproduces a number of different conditions around apoptosis including effects of different growth substrates and viral infections. It produces semi-quantitative predictions on the activity of individual nodes, agreeing with experimental data. The model (SBML format) and all data are available for further predictions and development.</p

Modeling the TNFα-Induced Apoptosis Pathway in Hepatocytes

The proinflammatory cytokine TNFα fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Recently, we showed that TNFα is able to sensitize primary murine hepatocytes cultured on collagen to Fas ligand-induced apoptosis and presented a mathematical model of the sensitizing effect. Here, we analyze how TNFα induces apoptosis in combination with the transcriptional inhibitor actinomycin D (ActD). Accumulation of reactive oxygen species (ROS) in response to TNFR activation turns out to be critical for sustained activation of JNK which then triggers mitochondrial pathway-dependent apoptosis. In addition, the amount of JNK is strongly upregulated in a ROS-dependent way. In contrast to TNFα plus cycloheximide no cFLIP degradation is observed suggesting a different apoptosis pathway in which the Itch-mediated cFLIP degradation and predominantly caspase-8 activation is not involved. Time-resolved data of the respective pro- and antiapoptotic factors are obtained and subjected to mathematical modeling. On the basis of these data we developed a mathematical model which reproduces the complex interplay regulating the phosphorylation status of JNK and generation of ROS. This model was fully integrated with our model of TNFα/Fas ligand sensitizing as well as with a published NF-κB-model. The resulting comprehensive model delivers insight in the dynamical interplay between the TNFα and FasL pathways, NF-κB and ROS and gives an example for successful model integration

Tumor necrosis factor sensitizes primary murine hepatocytes to Fas/CD95-induced apoptosis in a Bim- and Bid-dependent manner

Fas/CD95 is a critical mediator of cell death in many chronic and acute liver diseases and induces apoptosis in primary hepatocytes in vitro. In contrast, the proinflammatory cytokine tumor necrosis factor α (TNFα) fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Here we report that TNFα sensitizes primary murine hepatocytes cultured on collagen to Fas ligand (FasL)-induced apoptosis. This synergism is time-dependent and is specifically mediated by TNFα. Fas itself is essential for the sensitization, but neither Fas up-regulation nor endogenous FasL is responsible for this effect. Although FasL is shown to induce Bid-independent apoptosis in hepatocytes cultured on collagen, the sensitizing effect of TNFα is clearly dependent on Bid. Moreover, both c-Jun N-terminal kinase activation and Bim, another B cell lymphoma 2 homology domain 3 (BH3)-only protein, are crucial mediators of TNFα-induced apoptosis sensitization. Bim and Bid activate the mitochondrial amplification loop and induce cytochrome c release, a hallmark of type II apoptosis. The mechanism of TNFα-induced sensitization is supported by a mathematical model that correctly reproduces the biological findings. Finally, our results are physiologically relevant because TNFα also induces sensitivity to agonistic anti-Fas-induced liver damage. CONCLUSION: Our data suggest that TNFα can cooperate with FasL to induce hepatocyte apoptosis by activating the BH3-only proteins Bim and Bid

ON/OFF and beyond--a boolean model of apoptosis.

Apoptosis is regulated by several signaling pathways which are extensively linked by crosstalks. Boolean or logical modeling has become a promising approach to capture the qualitative behavior of such complex networks. Here we built a large-scale literature-based Boolean model of the central intrinsic and extrinsic apoptosis pathways as well as pathways connected with them. The model responds to several external stimuli such as Fas ligand, TNF-alpha, UV-B irradiation, interleukin-1beta and insulin. Timescales and multi-value node logic were used and turned out to be indispensable to reproduce the behavior of the apoptotic network. The coherence of the model was experimentally validated. Thereby an UV-B dose-effect is shown for the first time in mouse hepatocytes. Analysis of the model revealed a tight regulation emerging from high connectivity and spanning crosstalks and a particular importance of feedback loops. An unexpected feedback from Smac release to RIP could further increase complex II formation. The introduced Boolean model provides a comprehensive and coherent description of the apoptosis network behavior. It gives new insights into the complex interplay of pro- and antiapoptotic factors and can be easily expanded to other signaling pathways