Urinary tract infections (UTIs) are associated with a high rate of treatment failure, indicating that current antibiotic treatment strategies are not optimal. This project investigates the unexplored hypothesis that urine, the infection microenvironment in UTIs, may lead to distinctly different responses of bacterial pathogens to antibiotic treatments. We will perform unique translational experiments to evaluate to what extent urine can alter antibiotic treatment effects or affect the risk of developing antibiotic resistance. Results from these experiments are then used to design adapted antibiotic treatment strategies for UTIs to reduce treatment failure using mathematical modeling.

For good functioning of a protein, it must be folded in the correct way. Proteins undergo a complex process with multiple steps until they find their correct fold. In our cells, there are many molecules that could help with this complex process. As such there are special chaperone proteins that can protect folding proteins against the wrong steps. Multiple studies have studied this cooperation with single-molecule techniques, but have ignored the other molecules that can be found in a cell. Here we suggest a technique that studies the folding processes of a known model protein in the normal cellular environment.

Laboratory education is essential to prepare students for a research focused career. However, this education type is stressful for many students. In this project, videolabs will be developed to allow students to practice conducting their experiments prior to their lab day. The videolabs allow students to make mistakes and solve them without consequences for their research results. With these videolabs I create a new digital learning environment for laboratory education in which making mistakes becomes possible. It is expected that my students will be able to experience their laboratory education more stress-free and can also improve their learning results.

Most breast cancer associated deaths occur due to cancer spreading uncontrollably to other organs of the body, a process termed “metastasis”. This process is initiated by rare migratory cancer cells that possess an abnormal set of chemical reactions (i.e., metabolism) that fuel their migration. Investigating these rare cells, and the metabolic processes that fuel their migration is essential for identifying new treatments that can significantly improve patients’ prognosis. We aim to find key metabolic biomarkers related to this phenomenon using state of the art single-cell techniques. These biomarkers will be key for future treatments of resistant cancers.

Bacteriophage therapy has been proposed as an alternative novel treatment modality to address the global health threat of antimicrobial resistance. However, similar to antibiotics, bacterial pathogens develop resistance against bacteriophages. In this project we propose to experimentally characterize evolutionary trade-offs of resistance which can be exploited to restore treatment sensitivity of pathogens. Using an innovative mathematical model we translate the obtained experimental data into novel phage-antibiotic combination treatments which can reverse antimicrobial resistance.