How do cells respond to combinations of drugs and other signals? Can the evolution of antibiotic resistance be predicted and prevented? How do microbial ecosystems function? To tackle these and related questions, we combine concepts and techniques from physics with molecular biology and advanced high-throughput techniques. Our favorite model systems are E. coli and yeast but we are broadly interested in various other biological systems. To ultimately discover the general principles and laws of biology, we use a quantitative approach, i.e. whenever possible we measure and interpret numbers rather than pictures or qualitative effects.

Selected publications

1. de Vos, M.G.J., Zagorski, M., McNally, A., and Bollenbach, T. (2017). Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. Proc. Natl. Acad. Sci. U. S. A. 201713372 http://www.pnas.org/lookup/doi/10.1073/pnas.1713372114
2. Lukačišinová, M., and Bollenbach, T. (2017). Toward a quantitative understanding of antibiotic resistance evolution. Curr. Opin. Biotechnol. 46, 90–97 http://www.ncbi.nlm.nih.gov/pubmed/28292709 [Review].
3. Mitosch, K., Rieckh, G., and Bollenbach, T. (2017). Noisy Response to Antibiotic Stress Predicts Subsequent Single-Cell Survival in an Acidic Environment. Cell Syst. 4, 393–403.e5 http://dx.doi.org/10.1016/j.cels.2017.03.001
4. Zagorski, M., Tabata, Y., Brandenberg, N., Lutolf, M.P., Tkačik, G., Bollenbach, T.#, Briscoe, J.#, and Kicheva, A.# (2017) Decoding of position in the developing neural tube from antiparallel morphogen gradients. Science 356, 1379–1383 http://science.sciencemag.org/content/356/6345/1379
5. Bollenbach, T. (2015). Antimicrobial interactions: mechanisms and implications for drug discovery and resistance evolution. Curr. Opin. Microbiol. 27, 1–9 http://www.sciencedirect.com/science/article/pii/S1369527415000594 [Review].