Project A1

Cellular mechanisms of drug resistance evolution

Tobias Bollenbach, U Cologne | web | email

This project takes a systems-biology approach to the evolution of drug resistance in Escherichia coli. The central goal of this project is to increase the predictability of resistance evolution by systematically identifying genome-wide determinants and cellular pathways that affect the rate of adaptation. We address this goal using a combined approach of massively parallel experiments and model building.

Predictability in Evolution

Collaborative Research Center 1310

Publications

Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections

de Vos M.G.J., Zagorski M., McNally A., Bollenbach T., Proc. Natl. Acad. Sci. U. S. A. 114: 10666–10671, 3. October 2017,
https://doi.org/10.1073/pnas.1713372114

Decoding of position in the developing neural tube from antiparallel morphogen gradients

Zagorski M., Tabata Y., Brandenberg N., Lutolf M.P., Tkačik G., Bollenbach T., Briscoe J., Kicheva A., Science 356: 1379–1383, 30. June 2017,
https://doi.org/10.1126/science.aam5887

Dendritic Cells Interpret Haptotactic Chemokine Gradients in a Manner Governed by Signal-to-Noise Ratio and Dependent on GRK6

Schwarz J., Bierbaum V., Vaahtomeri K., Hauschild R., Brown M., de Vries I., Leithner A., Reversat A., Merrin J., Tarrant T., Bollenbach T., Sixt M.,
Curr. Biol. 27: 1314–1325, 27. April 2017, https://doi.org/10.1016/j.cub.2017.04.004

Noisy Response to Antibiotic Stress Predicts Subsequent Single-Cell Survival in an Acidic Environment

Mitosch K., Rieckh G., Bollenbach T., Cell Syst. 4: 393–403.e5, 22. March 2017, https://doi.org/10.1016/j.cels.2017.03.001

Toward a quantitative understanding of antibiotic resistance evolution

Lukačišinová M. & Bollenbach T., Curr. Opin. Biotechnol. 46: 90–97, 11. March 2017, https://doi.org/10.1016/j.copbio.2017.02.013

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