WP1: Integration of Epo-induced Signal Transduction

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SEEK ID: https://fairdomhub.org/investigations/102

Projects: SBEpo - Systems Biology of Erythropoietin

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Lorenz Adlung
Melania Barile
Andreas Franke
Bernhard Steiert
Marcel Schilling
Patricia Sauer
Christian Tönsing
Marie-Christine Wagner

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Maja Rey

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Created: 11th Oct 2016 at 09:24

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Lorenz Adlung

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

https://orcid.org/0000-0002-0971-2309

Expertise: Mathematical modelling, Single Cell analysis, Cell biology, Molecular Biology

Tools: Biochemistry, Systems Biology, Matlab, R

Melania Barile

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

Andreas Franke

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: Roche Diagnostics

Maja Rey

Projects: SysMO-LAB, de.NBI-SysBio, Kinetics on the move - Workshop 2016, Example use cases, SBEpo - Systems Biology of Erythropoietin, FAIRDOM & LiSyM & de.NBI Data Structuring Training, FAIRDOM, EnzymeML, FAIRDOM Community Workers, GMDS Project Group "FAIRe Dateninfrastrukturen für die Biomedizinische Informatik", MIX-UP, COVID-19 Disease Map, ERNEST Mapping Group Pilot Study, CC-TOP, SABIO-VIS, SDBV/HITS

Institutions: Heidelberg Institute for Theoretical Studies (HITS gGmbH)

Expertise: Biochemistry, Molecular Biology, Microbiology, Phytopathology, Data curation

Tools: SABIO-RK, SEEK

Within the de.NBI project my functions in the de.NBI-SysBio node comprise content curation, requirements elicitation, and community engagement for the users of biochemical reaction kinetics database SABIO-RK as well as of the data management platform SEEK.

Patricia Sauer

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

Marcel Schilling

Projects: SBEpo - Systems Biology of Erythropoietin, MS_DILI

Institutions: German Cancer Research Center (DKFZ)

https://orcid.org/0000-0002-9517-5166

Expertise: Systems Biology, Cell biology, Cell Cycle, Mathematical modelling, Cancer research, signal transduction, MAP-kinase

Bernhard Steiert

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: University of Freiburg

Christian Tönsing

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: University of Freiburg

https://orcid.org/0000-0003-2822-5191

Marie-Christine Wagner

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

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e:Bio

e:Bio - Innovations Competition Systems Biology

Projects: SulfoSys - Biotec, SBEpo - Systems Biology of Erythropoietin

Web page: http://www.fona.de/en/14276

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SBEpo - Systems Biology of Erythropoietin

Multi-level mathematical modeling of erythropoiesis for optimized expansion of erythroid progenitor cells and improved treatment regimes

Programme: e:Bio

Public web page: Not specified

Organisms: Homo sapiens, Mus musculus

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Protein abundance of AKT and ERK pathway components governs cell type-specific regulation of proliferation.

SBEpo - Systems Biology of Erythropoietin

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Lorenz Adlung

Marie-Christine Wagner

Sajib Chakraborty

Hauke Busch

Marcel Schilling

Abstract (Expand)

Signaling through the AKT and ERK pathways controls cell proliferation. However, the integrated regulation of this multistep process, involving signal processing, cell growth and cell cycle progression, … is poorly understood. Here, we study different hematopoietic cell types, in which AKT and ERK signaling is triggered by erythropoietin (Epo). Although these cell types share the molecular network topology for pro-proliferative Epo signaling, they exhibit distinct proliferative responses. Iterating quantitative experiments and mathematical modeling, we identify two molecular sources for cell type-specific proliferation. First, cell type-specific protein abundance patterns cause differential signal flow along the AKT and ERK pathways. Second, downstream regulators of both pathways have differential effects on proliferation, suggesting that protein synthesis is rate-limiting for faster cycling cells while slower cell cycles are controlled at the G1-S progression. The integrated mathematical model of Epo-driven proliferation explains cell type-specific effects of targeted AKT and ERK inhibitors and faithfully predicts, based on the protein abundance, anti-proliferative effects of inhibitors in primary human erythroid progenitor cells. Our findings suggest that the effectiveness of targeted cancer therapy might become predictable from protein abundance.

Authors: L. Adlung, S. Kar, M. C. Wagner, B. She, S. Chakraborty, J. Bao, S. Lattermann, M. Boerries, H. Busch, P. Wuchter, A. D. Ho, J. Timmer, M. Schilling, T. Hofer, U. Klingmuller

Date Published: 24th Jan 2017

Publication Type: Journal

PubMed ID: 28123004

Citation: Mol Syst Biol. 2017 Jan 24;13(1):904. doi: 10.15252/msb.20167258.

Created: 31st Jan 2017 at 13:05, Last updated: 8th Dec 2022 at 17:26

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.

SBEpo - Systems Biology of Erythropoietin

All authors

Bernhard Steiert

Marcel Schilling

Abstract (Expand)

Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs … such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Authors: R. Merkle, B. Steiert, F. Salopiata, S. Depner, A. Raue, N. Iwamoto, M. Schelker, H. Hass, M. Wasch, M. E. Bohm, O. Mucke, D. B. Lipka, C. Plass, W. D. Lehmann, C. Kreutz, J. Timmer, M. Schilling, U. Klingmuller

Date Published: 6th Aug 2016

Publication Type: Journal

PubMed ID: 27494133

Citation: PLoS Comput Biol. 2016 Aug 5;12(8):e1005049. doi: 10.1371/journal.pcbi.1005049. eCollection 2016 Aug.

Created: 13th Dec 2016 at 09:42, Last updated: 8th Dec 2022 at 17:26

Context-specific flow through the MEK/ERK module produces cell- and ligand-specific patterns of ERK single and double phosphorylation.

SBEpo - Systems Biology of Erythropoietin

All authors

Marcel Schilling

Abstract (Expand)

The same pathway, such as the mitogen-activated protein kinase (MAPK) pathway, can produce different cellular responses, depending on stimulus or cell type. We examined the phosphorylation dynamics of … the MAPK kinase MEK and its targets extracellular signal-regulated kinase 1 and 2 (ERK1/2) in primary hepatocytes and the transformed keratinocyte cell line HaCaT A5 exposed to either hepatocyte growth factor or interleukin-6. By combining quantitative mass spectrometry with dynamic modeling, we elucidated network structures for the reversible threonine and tyrosine phosphorylation of ERK in both cell types. In addition to differences in the phosphorylation and dephosphorylation reactions, the HaCaT network model required two feedback mechanisms, which, as the experimental data suggested, involved the induction of the dual-specificity phosphatase DUSP6 and the scaffold paxillin. We assayed and modeled the accumulation of the double-phosphorylated and active form of ERK1/2, as well as the dynamics of the changes in the monophosphorylated forms of ERK1/2. Modeling the differences in the dynamics of the changes in the distributions of the phosphorylated forms of ERK1/2 suggested that different amounts of MEK activity triggered context-specific responses, with primary hepatocytes favoring the formation of double-phosphorylated ERK1/2 and HaCaT A5 cells that produce both the threonine-phosphorylated and the double-phosphorylated form. These differences in phosphorylation distributions explained the threshold, sensitivity, and saturation of the ERK response. We extended the findings of differential ERK phosphorylation profiles to five additional cultured cell systems and matched liver tumor and normal tissue, which revealed context-specific patterns of the various forms of phosphorylated ERK.

Authors: N. Iwamoto, L. A. D'Alessandro, S. Depner, B. Hahn, B. A. Kramer, P. Lucarelli, A. Vlasov, M. Stepath, M. E. Bohm, D. Deharde, G. Damm, D. Seehofer, W. D. Lehmann, U. Klingmuller, M. Schilling

Date Published: 2nd Feb 2016

Publication Type: Journal

PubMed ID: 26838549

Citation: Sci Signal. 2016 Feb 2;9(413):ra13. doi: 10.1126/scisignal.aab1967.

Created: 13th Oct 2016 at 09:59, Last updated: 8th Dec 2022 at 17:26

Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

SBEpo - Systems Biology of Erythropoietin

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Bernhard Steiert

Christian Tönsing

Lorenz Adlung

Marcel Schilling

Abstract (Expand)

UNLABELLED: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of systems biology. Two of the most critical steps in this approach are to construct … dynamical models of biochemical reaction networks for large datasets and complex experimental conditions and to perform efficient and reliable parameter estimation for model fitting. We present a modeling environment for MATLAB that pioneers these challenges. The numerically expensive parts of the calculations such as the solving of the differential equations and of the associated sensitivity system are parallelized and automatically compiled into efficient C code. A variety of parameter estimation algorithms as well as frequentist and Bayesian methods for uncertainty analysis have been implemented and used on a range of applications that lead to publications. AVAILABILITY AND IMPLEMENTATION: The Data2Dynamics modeling environment is MATLAB based, open source and freely available at http://www.data2dynamics.org. CONTACT: andreas.raue@fdm.uni-freiburg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: A. Raue, B. Steiert, M. Schelker, C. Kreutz, T. Maiwald, H. Hass, J. Vanlier, C. Tonsing, L. Adlung, R. Engesser, W. Mader, T. Heinemann, J. Hasenauer, M. Schilling, T. Hofer, E. Klipp, F. Theis, U. Klingmuller, B. Schoberl, J. Timmer

Date Published: 1st Nov 2015

Publication Type: Journal

PubMed ID: 26142188

Citation: Bioinformatics. 2015 Nov 1;31(21):3558-60. doi: 10.1093/bioinformatics/btv405. Epub 2015 Jul 3.

Created: 13th Oct 2016 at 10:03, Last updated: 8th Dec 2022 at 17:26

Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

SBEpo - Systems Biology of Erythropoietin

All authors

Marcel Schilling

Abstract (Expand)

Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations … is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

Authors: L. A. D'Alessandro, R. Samaga, T. Maiwald, S. H. Rho, S. Bonefas, A. Raue, N. Iwamoto, A. Kienast, K. Waldow, R. Meyer, M. Schilling, J. Timmer, S. Klamt, U. Klingmuller

Date Published: 24th Apr 2015

Publication Type: Journal

PubMed ID: 25905717

Citation: PLoS Comput Biol. 2015 Apr 23;11(4):e1004192. doi: 10.1371/journal.pcbi.1004192. eCollection 2015 Apr.

Created: 11th Oct 2016 at 09:47, Last updated: 8th Dec 2022 at 17:26

Identification of isoform-specific dynamics in phosphorylation-dependent STAT5 dimerization by quantitative mass spectrometry and mathematical modeling.

SBEpo - Systems Biology of Erythropoietin

All authors

Lorenz Adlung

Marcel Schilling

Abstract (Expand)

STAT5A and STAT5B are important transcription factors that dimerize and transduce activation signals of cytokine receptors directly to the nucleus. A typical cytokine that mediates STAT5 activation is … erythropoietin (Epo). Differential functions of STAT5A and STAT5B have been reported. However, the extent to which phosphorylated STAT5A and STAT5B (pSTAT5A, pSTAT5B) form homo- or heterodimers is not understood, nor is how this might influence the signal transmission to the nucleus. To study this, we designed a concept to investigate the isoform-specific dimerization behavior of pSTAT5A and pSTAT5B that comprises isoform-specific immunoprecipitation (IP), measurement of the degree of phosphorylation, and isoform ratio determination between STAT5A and STAT5B. For the main analytical method, we employed quantitative label-free and -based mass spectrometry. For the cellular model system, we used Epo receptor (EpoR)-expressing BaF3 cells (BaF3-EpoR) stimulated with Epo. Three hypotheses of dimer formation between pSTAT5A and pSTAT5B were used to explain the analytical results by a static mathematical model: formation of (i) homodimers only, (ii) heterodimers only, and (iii) random formation of homo- and heterodimers. The best agreement between experimental data and model simulations was found for the last case. Dynamics of cytoplasmic STAT5 dimerization could be explained by distinct nuclear import rates and individual nuclear retention for homo- and heterodimers of phosphorylated STAT5.

Authors: M. E. Boehm, L. Adlung, M. Schilling, S. Roth, U. Klingmuller, W. D. Lehmann

Date Published: 5th Dec 2014

Publication Type: Journal

PubMed ID: 25333863

Citation: J Proteome Res. 2014 Dec 5;13(12):5685-94. doi: 10.1021/pr5006923. Epub 2014 Nov 7.

Created: 13th Oct 2016 at 10:10, Last updated: 8th Dec 2022 at 17:26

Covering a broad dynamic range: information processing at the erythropoietin receptor.

SBEpo - Systems Biology of Erythropoietin

All authors

Marcel Schilling

Abstract (Expand)

Cell surface receptors convert extracellular cues into receptor activation, thereby triggering intracellular signaling networks and controlling cellular decisions. A major unresolved issue is the … identification of receptor properties that critically determine processing of ligand-encoded information. We show by mathematical modeling of quantitative data and experimental validation that rapid ligand depletion and replenishment of the cell surface receptor are characteristic features of the erythropoietin (Epo) receptor (EpoR). The amount of Epo-EpoR complexes and EpoR activation integrated over time corresponds linearly to ligand input; this process is carried out over a broad range of ligand concentrations. This relation depends solely on EpoR turnover independent of ligand binding, which suggests an essential role of large intracellular receptor pools. These receptor properties enable the system to cope with basal and acute demand in the hematopoietic system.

Authors: V. Becker, M. Schilling, J. Bachmann, U. Baumann, A. Raue, T. Maiwald, J. Timmer, U. Klingmuller

Date Published: 11th Jun 2010

Publication Type: Journal

PubMed ID: 20488988

Citation: Science. 2010 Jun 11;328(5984):1404-8. doi: 10.1126/science.1184913. Epub 2010 May 20.

Created: 13th Oct 2016 at 11:24, Last updated: 8th Dec 2022 at 17:26