The overall goal of the toxicology research group is risk evaluation of chemicals based on precise knowledge of the molecular mechanisms that induce adverse effects. The specific contribution of the SysTox group is to develop and apply methods in systems biology to integrate data generated by the individual research groups of the Department of Toxicology into mathematical models. Based on model simulations, responses at the molecular, cellular, and organ level can be predicted.
Crucial strategic developments during the past years include:
(i) the establishment of spatio-temporal models with the possibility to integrate metabolic pathways and signalling networks (Drasdo et al., 2014; Hoehme et al., 2010). This allows to understand and to quantitatively predict metabolic consequences of exposure to toxic compounds (Ghallab et al., 2016; Schliess et al., 2014; Vartak et al., 2016). Moreover, basic aspects of subcellular mechanisms can be simulated, such as control mechanisms of the number and size of organelles (Zeigerer et al., 2012);
(ii) the establishment of state of the art techniques to analyse and model time-resolved genome-wide data (Frey et al., 2014). This allows the evaluation of cell states during differentiation of stem cells (Godoy et al., 2015), characterisation of the influence of toxic compounds and the identification of susceptibility genes (Rothman et al., 2010);
(iii) the establishment of two-photon based functional intravital imaging. This technique can be applied to cell cultures as well as to intact organs of anaesthetised mice to quantify transport of endogenous compounds or xenobiotics, mitochondrial potential, and activation of receptors using functional sensors (Jansen et al., 2017). Since the generated data are time-resolved and quantitative, they are appropriate for integration into the aforementioned models.
A strategic challenge of the SysTox group is the expectation to contribute to both, internationally competitive basic research work in toxicology and also the transfer of newly established techniques and knowledge into application. To meet these requirements SysTox scientists join research networks in adequate areas of basic science (e.g. the BMBF funded project ‘Systems Medicine of the Liver’) and also applied projects in the field of toxicological risk evaluation such as EU-ToxRisk. Recently, internationally recognised experts Dr. Nachiket Vartak (Vartak et al., 2014, 2016; Schmick et al., 2014; Zimmermann et al., 2013), Dr. Dirk Drasdo (Drasdo et al., 2014; Schliess et al., 2014; Hoehme et al., 2010) and Dr. Karolina Edlund (Uhlen et al., 2015) have joined our group.
Drasdo D, Hoehme S, Hengstler JG: How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis. J Hepatol 61: 951-956 (2014)
Frey O, Misun PM, Fluri DA, Hengstler JG, Hierlemann A: Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis. Nat Commun 5: 4250 (2014) (11 pp)
Ghallab A, Cellière G, Henkel SG, …, Godoy P, …, Blaszkewicz M, Reif R, Marchan R, …Drasdo D, …, Hengstler JG: Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases. J Hepatol 64: 860-871 (2016)
Godoy P, Schmidt-Heck W, Natarajan K, …, Widera A, Stoeber R, Campos G, Hammad S, …, Edlund K, …, Hengstler JG: Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells. J Hepatol 63: 934-942 (2015)
Hoehme S, Brulport M, Bauer A, Bedawy E, Schormann W, Hermes M, …, Hengstler JG, Drasdo D: Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc Natl Acad Sci U S A 107: 10371-10376 (2010)
Kiemeney LA, Sulem P, Besenbacher S, … , Hengstler JG, Blaszkewicz M, …, Golka K, …, Stefansson K: A sequence variant at 4p16.3 confers susceptibility to urinary bladder cancer. Nat Genet 42: 415-419 (2010)
Krug AK, Kolde R, Gaspar JA, Rempel E, …, Marchan R,…, van Thriel C, …, Hengstler JG, …, Sachinidis A: Human embryonic stem cell-derived test systems for developmental neurotoxicity: a transcriptomics approach. Arch Toxicol 87: 123-143 (2013)
Rothman N, Garcia-Closas M, Chatterjee N, …, Golka K, …, Selinski S, Hengstler JG, …, Chanock SJ: A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci. Nat Genet 42: 978-984 (2010)
Schliess F, Hoehme S, Henkel SG, Ghallab A, …, Hengstler JG, …, Drasdo D, Zellmer S: Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration. Hepatology 60: 2040-2051 (2014)
Schmick M, Vartak N, Papke B, Kovacevic M, Truxius DC, Rossmannek L, Bastiaens PI: KRas localizes to the plasma membrane by spatial cycles of solubilization, trapping and vesicular transport. Cell 157: 459–471 (2014)
Stewart JD, Marchan R, Lesjak MS, Lambert J, Hergenroeder R, Ellis JK, Lau CH, Hengstler JG: Choline-releasing glycerophosphodiesterase EDI3 drives tumor cell migration and metastasis. Proc Natl Acad Sci USA 109: 8155-8160 (2012)
Uhlén M, Fagerberg L, Hallstroem BM, …, Edlund K, …, Pontén F: Tissue-based map of the human proteome. Science 347 (6220): 1260419 (2015)
Vartak N, Papke B, Grecco HE, Rossmannek L, Waldmann H, Hedberg C, Bastiaens PI: The autodepalmitoylating activity of APT maintains the spatial organization of palmitoylated membrane proteins. Biophys J 106: 93–105 (2014)
Vartak N, Damle-Vartak A, Richter B, Dirsch O, Dahmen U, Hammad S, Hengstler JG: Cholestasis-induced adaptive remodeling of interlobular bile ducts. Hepatology 63: 951-964 (2016)
Zeigerer A, Gilleron J, Bogorad RL, …, Hengstler JG, …, Zerial M: Rab5 is necessary for the biogenesis of the endolysosomal system in vivo. Nature 485(7399): 465-470 (2012)
Zimmermann G, Papke B, Ismail S, Vartak N, Chandra A, Hoffmann M, Hahn SA, Triola G, Wittinghofer A, Bastiaens PI, Waldmann H: Small molecule inhibition of the KRAS-PDEδ interaction impairs oncogenic KRAS signalling. Nature 497(7451): 638-642 (2013)