BackgroundMost of the modeling performed in the area of systems biology aims at achieving a quantitative description of the intracellular pathways within a "typical cell". However, in many biologically important situations even clonal cell populations can show a heterogeneous response. These situations require study of cell-to-cell variability and the development of models for heterogeneous cell populations.ResultsIn this paper we consider cell populations in which the dynamics of every single cell is captured by a parameter dependent differential equation. Differences among cells are modeled by differences in parameters which are subject to a probability density. A novel Bayesian approach is presented to infer this probability density from population snapshot data, such as flow cytometric analysis, which do not provide single cell time series data. The presented approach can deal with sparse and noisy measurement data. Furthermore, it is appealing from an application point of view as in contrast to other methods the uncertainty of the resulting parameter distribution can directly be assessed.ConclusionsThe proposed method is evaluated using artificial experimental data from a model of the tumor necrosis factor signaling network. We demonstrate that the methods are computationally efficient and yield good estimation result even for sparse data sets.

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In response to deregulated oncogene activation, mammalian cells activate disposal programs such as programmed cell death. To investigate the mechanisms behind this oncogenic stress response we used Bcr-Abl over-expressing cells cultivated in presence of imatinib. Imatinib deprivation led to rapid induction of Bcr-Abl activity and over-stimulation of PI3K/Akt-, Ras/MAPK-, and JAK/STAT pathways. This resulted in a delayed necrosis-like cell death starting not before 48 hours after imatinib withdrawal. Cell death was preceded by enhanced glycolysis, glutaminolysis, and amino acid metabolism leading to elevated ATP and protein levels. This enhanced metabolism could be linked to induction of cell death as inhibition of glycolysis or glutaminolysis was sufficient to sustain cell viability. Therefore, these data provide first evidence that metabolic changes induced by Bcr-Abl hyper-activation are important mediators of oncogenic stress-induced cell death.During the first 30 hours after imatinib deprivation, Bcr-Abl hyper-activation did not affect proliferation but resulted in cellular swelling, vacuolization, and induction of eIF2α phosphorylation, CHOP expression, as well as alternative splicing of XPB, indicating endoplasmic reticulum stress response. Cell death was dependent on p38 and RIP1 signaling, whereas classical death effectors of ER stress, namely CHOP-BIM were antagonized by concomitant up-regulation of Bcl-xL.Screening of 1,120 compounds for their potential effects on oncogenic stress-induced cell death uncovered that corticosteroids antagonize cell death upon Bcr-Abl hyper-activation by normalizing cellular metabolism. This protective effect is further demonstrated by the finding that corticosteroids rendered lymphocytes permissive to the transforming activity of Bcr-Abl. As corticosteroids are used together with imatinib for treatment of Bcr-Abl positive acute lymphoblastic leukemia these data could have important implications for the design of combination therapy protocols.In conclusion, excessive induction of Warburg type metabolic alterations can cause cell death. Our data indicate that these metabolic changes are major mediators of oncogenic stress induced by Bcr-Abl.

TNF-related apoptosis-inducing ligand (TRAIL) is a member of the tumor necrosis factor (TNF) ligand family that exerts its apoptotic activity in human cells by binding to two transmembrane receptors, TRAILR1 and TRAILR2. In cells co-expressing both receptors the particular contribution of either protein to the overall cellular response is not well defined. Here we have investigated whether differences in the signaling capacities of TRAILR1 and TRAILR2 can be attributed to certain functional molecular subdomains. We generated and characterized various chimeric receptors comprising TRAIL receptor domains fused with parts from other members of the TNF death receptor family. This allowed us to compare the contribution of particular domains of the two TRAIL receptors to the overall apoptotic response and to identify elements that regulate apoptotic signaling. Our results show that the TRAIL receptor death domains are weak apoptosis inducers compared to those of CD95/Fas, because TRAILR-derived constructs containing the CD95/Fas death domain possessed strongly enhanced apoptotic capabilities. Importantly, major differences in the signaling strengths of the two TRAIL receptors were linked to their transmembrane domains in combination with the adjacent extracellular stalk regions. This was evident from receptor chimeras comprising the extracellular part of TNFR1 and the intracellular signaling part of CD95/Fas. Both receptor chimeras showed comparable ligand binding affinities and internalization kinetics. However, the respective TRAILR2-derived molecule more efficiently induced apoptosis. It also activated caspase-8 and caspase-3 more strongly and more quickly, albeit being expressed at lower levels. These results suggest that the transmembrane domains together with their adjacent stalk regions can play a major role in control of death receptor activation thereby contributing to cell type specific differences in TRAILR1 and TRAILR2 signaling.