Our main research interest is to understand how molecular networks within cells such as signal transduction cascades or gene regulatory networks process information.

Our group uses methods from mathematical modeling, bioinformatics and quantitative cell biology to investigate how structure and dynamics of networks relate to their biological function. Specifically, the main research aim of the group is to understand how oncogenic signaling pathways and their downstream gene regulatory networks mediate their oncogenic potential, how drugs can effectively modulate these networks and how resistance against targeted kinase inhibitors arises. Other research interests include dynamics of differentiation processes, how promoters integrate different signals, and how transcriptional and post-transcriptional regulation cooperate to generate specificity and reliability in gene expression.

We work in close interplay between experiments, theory and computation.

Some of the key questions we are interested in are:

  • How do cells discriminate between short and long signals? Why do chronic signals (such as induced by oncogenes) trigger other transcriptional programmes than transient signals? (see e.g. Uhlitz et al, 2017).
  • What is the role of ubiquitiously found feedbacks in signalling? What are the consequences of these fedbacks for targeted inhibitors (see e.g. Klinger et al, 2013 and Fritsche-Guenther et al, 2011).
  • The dose of proteins varyies strongly between individual clonal cells. How can cells deal with it? What are the mechanisms that control protein dose? (Schmiedel et al, 2015, Fritsche-Guenter et al, 2011)

To address these questions, we generate quantitative or genome-wide experimental data. We analyse and integrate these data using state-of-the-art bioinformatical methods and mathematical models.

Our infrastructure was supported by the Stiftung Charite, and the IRI Life Sciences. Our research projects are funded by the German Ministry of Education and Research (BMBF), the Deutsche Forschungsgemeinschaft (DFG), Deutsches Konsortium für translationale Krebsforschung (DKTK) and the Berlin Institute of Health through various grants.



Key publications

  1. Georg, P. *; Astaburuaga-Garcia, R. *; Bonaguro, L. *; Brumhard, S.; Michalick, L.; Lippert, L. J.; Kostevc, T.; Gäbel, C.; Schneider, M.; Streitz, M.; Demichev, V.; Gemünd, I.; Barone, M.; Tober-Lau, P.; Helbig, E. T.; Hillus, D.; Petrov, L.; Stein, J.; Dey, H-P.; Paclik, D.; Iwert, C.; Mülleder, M.; Aulakh, S. K.; Djudjaj, S.; Bülow, R. D.; Mei, H. E.; Schulz, A. R.; Thiel, A.; Hippenstiel, S.; Saliba, A-E.; Eils, R.; Lehmann, I.; Mall, M. A.; Stricker, S.; Röhmel, J.; Corman, V. M.; Beule, D.; Wyler, E.; Landthaler, M.; Obermayer, B.; von Stillfried, S.; Boor, P.; Demir, M.; Wesselmann, H.; Suttorp, N.; Uhrig, A.; Müller-Redetzky, H.; Nattermann, J.; Kuebler, W. M.; Meisel, C.; Ralser, M.; Schultze, J. L.; Aschenbrenner, A. C.; Thibeault, C.; Kurth, F.; Sander, L. E. *; Blüthgen, N. * and Sawitzki, B. *
    Complement activation induces excessive T cell cytotoxicity in severe COVID-19.
    Cell, 185: 493-512, 2022. doi 
  2. Dorel, M; Klinger, B; Mari, T; Toedling, J; Blanc, E; Messerschmidt, C; Nadler-Holly, M; Ziehm, M; Sieber, A; Hertwig, F; Beule, D; Eggert, A; Schulte, J H; Selbach, M and Blüthgen, N
    Neuroblastoma signalling models unveil combination therapies targeting feedback-mediated resistance.
    PLoS Comput Biol, 17: e1009515, 2021. doi  pubmed 
  3. Bischoff, P; Trinks, A; Obermayer, B; Pett, JP; Wiederspahn, J; Uhlitz, F; Liang, X; Lehmann, A; Jurmeister, P; Elsner, A; Dziodzio, T; Rückert, JC; Neudecker, J; Falk, C; Beule, D; Sers, C; Morkel, M; Horst, D; Blüthgen, N * and Klauschen, F *
    Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma.
    Oncogene, 40: 6748-6758, 2021. doi  pubmed 
  4. Uhlitz, F *; Bischoff, P *; Peidli, S *; Sieber, A; Trinks, A; Lüthen, M; Obermayer, B; Blanc, E; Ruchiy, Y; Sell, T; Mamlouk, S; Arsie, R; Wei, T T; Klotz-Noack, K; Schwarz, R F; Sawitzki, B; Kamphues, C; Beule, D; Landthaler, M; Sers, C; Horst, D; Blüthgen, N * and Morkel, M *
    Mitogen-activated protein kinase activity drives cell trajectories in colorectal cancer.
    EMBO Mol Med., 13: e14123, 2021. doi  pubmed 
  5. Brandt, R. *; Sell, T. *; Lüthen, M.; Uhlitz, F.; Klinger, B.; Riemer, P.; Giesecke-Thiel, C.; Schulze, S.; El-Shimy, I. A.; Kunkel, D.; Fauler, B.; Mielke, T.; Mages, N.; Herrmann, B. G; Sers, C.; Blüthgen, N. * and Morkel, M. *
    Cell type-dependent differential activation of ERK by oncogenic KRAS in colon cancer and intestinal epithelium.
    Nature communications, 10 (1): 2919, 2019. doi 
  6. Bischoff, P; Trinks, A; Wiederspahn, J; Obermayer, B; Pett, JP; Jurmeister, P; Elsner, A; Dziodzio, T; Rückert, JC; Neudecker, J; Falk, C; Beule, D; Sers, C; Morkel, M; Horst, D; Klauschen, F and Blüthgen, N
    The single-cell transcriptional landscape of lung carcinoid tumors.
    Int J Cancer, early online, 2022. doi  pubmed 
  7. Gross, T.; Wongchenko, M.; Yan, Y. and Blüthgen, N.
    Robust network inference using response logic.
    Bioinformatics, 35: i634–i642, 2019. doi 
  8. Dorel, M.; Klinger, B.; Sieber, A.; Prahallad, A.; Gross, T.; Bosdriesz, E.; Wessels, L. and Blüthgen, N.
    Modelling Signalling Networks from Perturbation Data.
    Bioinformatics, 34: 4079-4086, 2018. doi  pubmed 
  9. Uhlitz, F.; Sieber, A.; Wyler, E.; Fritsche-Guenther, R.; Meisig, J.; Landthaler, M.; Klinger, B. and Blüthgen, N.
    An immediate-late gene expression module decodes ERK signal duration.
    Molecular Systems Biology, 13: 928, 2017. doi 
  10. Schmiedel, J.M.; Klemm, S.; Zheng, Y.; Sahay, A.; Blüthgen, N. *; Marks, D.S. * and Oudenaarden, A.v. *
MicroRNA control of protein expression noise.
    Science, 348: 128-132, 2015. doi  pubmed 
  11. Klinger, B.; Sieber, A.; Fritsche-Guenther, R.; Witzel, F.; Berry, L.; Schumacher, D.; Yan, Y.; Durek, P.; Merchant, M.; Schäfer, R.; Sers, C. and Blüthgen, N.
    Network quantification of EGFR signaling unveils potential for targeted combination therapy.
    Molecular Systems Biology, 9: 673, 2013. doi  pubmed 
  12. Fritsche-Guenther, R.; Witzel, F.; Sieber, A.; Herr, R.; Schmidt, N.; Braun, S.; Brummer, T.; Sers, C. and Blüthgen, N.
    Strong negative feedback from Erk to Raf confers robustness to MAPK signalling.
    Mol Syst Biol, 7: 489, 2011. doi  pubmed