Addressing Antimicrobial Resistance through Advanced UTI Models

Urinary tract infections (UTIs) remain a major global health challenge, with high recurrence rates and growing antimicrobial resistance contributing to an estimated 260,000 deaths annually. Current laboratory susceptibility tests often fail to predict real-world treatment outcomes, underscoring the need for physiologically relevant infection models.

A recent study led by Beyond Antibiotics researcher, Dr Ramon Garcia Maset, in collaboration with Dr Aaron Crowther and Mr Davide De Grandi, who were co-supervised by Prof Jennifer Rohn at University College London and Dr Dario Carugo at the University of Oxford, deploys innovative models as platforms to better replicate the bladder environment:

• 3D-UHU – a three-dimensional urothelial microtissue model
• P-FLO – a novel mesofluidic system incorporating realistic flow dynamics

The team showed that microenvironmental complexity and mechanical forces significantly influenced the behaviour of uropathogenic E. coli and the effectiveness of antibiotics and bacteriophages. While nitrofurantoin showed strong activity in standard assays, it was less effective in advanced models. Similarly, bacteriophage therapy and combination treatments demonstrated variable performance depending on physiological conditions and flow dynamics.

Implications for Antimicrobial Resistance:

• Conventional testing may overestimate drug efficacy, risking treatment failure (and consequently, antibiotic prescriptions that don’t work as intended, necessitating further treatments down the road)
• Physiologically informed models are essential to design therapies that work in real infection environments
• Understanding host-pathogen interactions under realistic conditions can guide treatment strategies beyond traditional antibiotics or help maintain the effectiveness of existing antibiotics  

Read the pre-print here: Effect of human urinary microenvironment and fluid flow on antibiotic and phage therapy efficacy against uropathogenic Escherichia coli | bioRxiv

This research is funded by the Engineering and Physical Science Research Council (EPSRC) Programme Grant Scheme under the reference number EP/V026623/1.