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Multiscale modeling and simulations to bridge molecular and cellular scales

Using integrated multiscale models to guide experimental decisions and designs: Lessons from drug-induced liver damage, its functional consequences and regeneration

speaker: Dirk Drasdo (Leipzig)

abstract: In vivo experiments are expensive, time consuming, and underlie strict ethic rules. Their results only partially apply to human. Modern experimental methods composed of imaging at high res- olution, in 3D, or in living tissues provide information that increasingly permit development and parameterization of multi-level computational models, that allow for virtual experiments. In such models, hypotheses on molecular, cell-level or tissue-level mechanisms can be implemented and their consequence been tested in-silico. The results can be used to guide experimental decisions and de- signs (Drasdo et. al., J. Hepat. 2014). Prospectively, this can permit feeding computational models with patient-speci c information at each of the above levels and studying the prospective impact of therapeutic interventions. As a step towards a virtual liver lobule, we in this presentation will report stepwise the development of a multilevel model of drug-induced damage, regeneration and the detoxi cation of ammonia during regeneration. Hyperammonemia (too high ammonia blood concentration) is a severe complication after drug induced liver damage, for example resulting from overdosing acetaminophen (paracetamol), and can lead to encephalopathy and dead of the patient. We will rst present an integrated model, integrating a compartment model of ammonia detoxi ca- tion and a spatial-temporal micro-architectural agent-based model of liver regeneration after drug induced liver damage, that was able to identify lack of a critical ammonia sink mechanism in the 40-years old consensus reaction scheme (Schliess et. al., Hepatology, 2014). The nding has led to identi cation of a so far unrecognized ammonia sink mechanism that could be experimentally demonstrated to represent a potential therapy approach in hyperammonemia (Ghallab et. al, J. Hepat. 2016). In a further step we redo the analysis in a full spatial temporal micro-architecture model of the smallest virtual functional micro-anatomical unit (called lobule) obtained from image analysis (Hammad et. al., Arch. Toxicol. 2014; Friebel et. al., Bioinformatics, 2015) whereby the detoxi cation reactions are executed in each individual hepatocyte. Unlike the integrative model, the spatial-temporal multiscale model is able to predict the consequences of architectural distortions as they occur in liver brosis on liver metabolism. Finally, we extend the multiscale model by in- tegrating a model of toxic damage by acetaminophen in each hepatocyte, as well as HGF - induced cell progression during the regeneration of tissue damage caused by acetaminophen.

References Drasdo, D., Hoehme, S., Hengstler, JG. How predictive quantitative modeling of tissue organiza- tion can inform liver disease pathogenesis. Journal of Hepatology, Volume 61, Issue 4, October 2014, pp 951-956. Friebel, A., Neitsch, J., Johann, T., et. al. (shared senior authors). TiQuant: Software for tissue analysis, quanti cation and surface reconstruction. Bioinformatics 2015. doi: 10.1093bioin- formaticsbtv346. Jun 3. Ghallab, A., Henkel, S.G., Cellire, et al. Model guided identi cation and therapeutic implications of an ammonia sink mechanism. J. Hepat, 64(4):860-71, doi: 10.1016j.jhep.2015.11.018. Hammad S., Hoehme S., Friebel A., et. al. Protocols for staining of bile canalicular and sinusoidal networks of human, mouse and pig livers, three-dimensional reconstruction and quanti cation of tissue microarchitecture by image processing and analysis. Arch. of Toxicol. 88 (5) 1161-1183 (2014) Hoehme, S., Brulport, M., Bauer, A., et. al. (2010). Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc. Natl. Acad. Sci. (USA), 107(23), 10371-10376. Schliess, F., Hoehme, S., Henkel, S., et. al.. 2014. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxi cation during liver damage and regeneration. Hepatology 60 6, 204051.


timetable:
Fri 5 Oct, 11:00 - 12:15, Aula Dini
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