PhD Host-Pathogen Interactions During Urinary Tract Infection as Drivers of Chronic Neurological Disease

Details

Synopsis: This project will investigate how urinary tract infection (UTI) and host–pathogen interactions affect the brain and how to prevent this, since this is a major problem of unmet clinical need. Concurrent with peripheral immune responses, neurovascular integrity and brain molecular pathways associated with neurological vulnerability will be studied, along with behaviour, further integrated with human rUTI cohorts and rescue experiments to identify translational host-response signatures linking peripheral infection to brain dysfunction relevant to many early and late-life clinical situations.

Rationale and Background: Urinary tract infection (UTI) is among the most common bacterial infection worldwide and represent a major source of systemic inflammation across the lifespan. In older adults, UTI is a leading precipitant of delirium and are strongly associated with accelerated cognitive decline and worsening of dementia and is the leading cause of hospital admission for dementia patients. In addition, emerging clinical and epidemiological evidence suggests that the neurological consequences of peripheral infections extend beyond ageing populations. Recurrent or severe UTI has also been linked to increased risk of psychiatric disorders, including depression and psychosis, highlighting a broader interaction between infection biology and brain function. UTI is most commonly caused by uropathogenic Escherichia coli (UPEC), yet the biological mechanisms through which host–pathogen interactions during infection shape systemic immune responses, neurovascular integrity and long-term neurological vulnerability remain poorly understood.

Objectives and Methodology: Our laboratory has established a murine UTI model using uropathogenic Escherichia coli (UPEC) and generated unpublished data demonstrating infection-associated alterations in brain single-cell transcriptomic profiles, supporting feasibility and motivating a systems-level investigation of host–pathogen interactions and brain responses.

Objective 1: Determine how host–pathogen interactions during UTI influence brain pathology and behaviour.

UTI will be induced in wild-type mice via transurethral catheterisation with uropathogenic Escherichia coli (UPEC). To account for variability in host–pathogen interactions, a small panel of clinically relevant UPEC isolates (~5 strains) from the established E. coli strain collection will initially be tested to establish the infection model and assess differences in infection severity and systemic inflammatory responses. A representative strain producing reproducible infection will then be selected for detailed neurological analyses. Behavioural testing will assess spatial memory using radial arm maze and Barnes maze tasks. Infection severity will be quantified by colony-forming unit (CFU) counts from bladder and kidney tissues, alongside systemic immune profiling including cytokine measurements (e.g. IL-6, TNF-α, IL-1β, IFN-γ) and immune cell analysis. Brain tissue will be examined to assess neurovascular integrity and neuroinflammation, including blood–brain barrier disruption, endothelial junction protein expression and glial activation. Forebrain tissue will undergo single-nucleus RNA sequencing to identify cell-type-specific transcriptional responses to infection.

Objective 2: Determine how recurrent host–pathogen interactions during UTI drive cumulative neurovascular dysfunction and behavioural deficits.

To model clinically relevant recurrent infection, recurrent UTI (rUTI) will be induced in wild-type mice. Behavioural, immunological, histopathological and transcriptomic analyses will be performed as in Objective 1 to determine whether rUTI produces cumulative neurovascular and molecular alterations in the brain. Omics analyses will be used to identify candidate pathways associated with persistent neurovascular dysfunction, glial activation and behavioural deficits. Prioritised pathways will then be selected for targeted validation, and proof-of-concept rescue experiments will assess whether modulation of these pathways can attenuate infection-associated pathology.

Objective 3: Establish translational relevance using a human rUTI pilot cohort.

In collaboration with Dr Megan Perry, a consultant in Edinburgh in infectious disease with expertise in rUTI, urine and blood samples will be collected from individuals with acute or rUTI alongside basic clinical metadata and microbiology results. Peripheral immune markers will be quantified to define host-response signatures. These human immune profiles will be compared with the peripheral signatures that predict neurovascular dysfunction and brain transcriptomic vulnerability in the mouse models, providing a translational test of the infection–host response pathway linking peripheral infection to neurological disease risk.

The supervisory team integrates expertise in UPEC pathogenesis (Gally), neurovascular mechanisms of neurodegeneration (Qiu), and data science (Seth), enabling identification of host–pathogen molecular signatures associated with neurodegenerative vulnerability.

Potential impact: This project may identify host–pathogen immune signatures that drive neurovascular dysfunction following infection. These findings, coupled with animal model rescue experiments will inform therapeutic strategies targeting infection-driven neuroinflammation, improve management of rUTI, and help develop interventions aimed at reducing infection-associated risk of neurological disease.

Training: This project will provide rigorous interdisciplinary training at the interface of infection biology, neurovascular neuroscience, behaviour, and quantitative data science. The student will gain hands-on expertise in murine UPEC infection models, host–pathogen interaction assays, systemic immune profiling, blood–brain barrier analysis and behavioural assessment. Training in robust experimental design, reproducibility, and ethical animal research will be embedded throughout.

A central component of development will be advanced computational and data science training. The student will receive structured instruction in RNA-seq processing, quality control, differential expression analysis, multivariate modelling, and network analysis. They will learn to integrate multi-modal datasets (infection burden, immune markers, neurovascular outcomes and transcriptomics in human and animal model situations) to identify predictive molecular signatures and therapeutic strategies. Emphasis will be placed on reproducible research practices and data management.

Recruitment: This interdisciplinary project will suit a highly motivated candidate with a strong academic background in either biomedical sciences, neuroscience, immunology, microbiology, bioinformatics or a related field. Applicants should hold (or expect to obtain) a first-class or strong upper second-class honours degree (or equivalent). Prior experience in a subset of molecular or cellular biology, neuroscience, infection models, immunological techniques, vascular biology or animal research would be advantageous but not essential. Given the quantitative component, familiarity with statistics, coding (e.g. R or Python) or transcriptomic data analysis would be beneficial.

Apply: All applications must be submitted through the Future Medicine PhD fellowships website.