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Antibiotic treatments are sometimes not as effective against bacteria as we would want them to be. Bacterial populations make use of sensing and bet-hedging strategies to be least susceptible to the dynamic drug concentrations within their environment. If they do this successfully, they reserve time to develop antibiotic resistance. Because of this smart adaptation, both phenotypically and genetically, they are sometimes able to resume growth.

During my PhD, I am looking more closely into this adaptation, using E.coli as a model organism. I am interested in the evolutionary constraints and will explore these by performing long-term experiments in dynamic antibiotic environments. Furthermore, I will aim for a more quantitative description of single-cell growth in such environments, to see how phenotypic subpopulations contribute to survivability, using flow-cytometry


Courses attended

  • Scientific integrity
  • Pitch presentations (FAMElab)
  • Preventing performance anxiety
  • Programming in Matlab
  • ODE modeling in Systems Biology


Internship supervision

  • Gabriela Goncalves Nicolau (Bachelor, 5 months)
  • Max Guillaume (Master, 7 months)

Education / Academic qualification

Systems Biology and Bioinformatics, Master, University of Amsterdam

1 Sep 20131 Aug 2015

Biology, Bachelor, Wageningen University

1 Sep 20091 Aug 2012

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Research Output 2017 2018

Alignment of microbial fitness with engineered product formation: obligatory coupling between acetate production and photoautotrophic growth

Du, W., Jongbloets, J. A., van Boxtel, C., Hernández, H. P., Lips, D., Olivier, B. G., Hellingwerf, K. J. & dos Santos, F. B. 13 Feb 2018 In : Biotechnology for Biofuels. 11, 38, p. 1-13

Research output: Scientific - peer-reviewArticle