This project will test the hypothesis that stress response markers and behavioural changes can predict chronic disease outcomes—specifically for epilepsy—in Theiler’s murine encephalomyelitis virus (TMEV)-induced encephalitis. The long-term goal is to improve characterisation of epileptogenesis and identify biomarkers that indicate optimal therapeutic windows to prevent or modify disease progression after CNS viral infections.

To align with 3R principles, the project will include:

• Use peripheral blood markers instead of invasive brain immunohistology
• Apply AI-assisted behavioural analysis in place of long-term EEG recordings
• Reduce animal numbers in chronic studies by identifying epileptic animals early, before chronic seizures occur, using blood and behavioural biomarkers

Additionally, TMEV-induced neuronal changes will be studied to assess their predictive value for epilepsy onset.

Project P02 aims to investigate whether immune and stress responses caused by two intestinal parasite infections can be detected in exfoliated mucosal cells (EMC).

• A novel, non-invasive method will be developed in mice to monitor the onset, intensity, and duration of these responses
• The project also explores how these infections affect host behaviour
• Long-term goal is to use this EMC-based approach to refine experimental procedures and reduce data variability and animal group sizes in infectious disease research
  
  
  
  
  
  

This project investigates long-term neurological complications following neonatal infection with Listeria monocytogenes (Lm) in mice. By comparing infections with both wild-type and avirulent mutant strains, the study aims to assess chronic behavioural, cognitive, and memory-related effects in adult survivors.

Key objectives include:

• Defining functional consequences of early-life Lm infection
• Identifying neurological and behavioural sequelae
• Studying brain homeostasis, stress profiles, and cellular alterations
• Exploring cell tropism and how Lm affects specific neuronal cell types

Ultimately, the findings will inform termination criteria for future experiments, significantly improving animal welfare by refining the use of neonatal infection models.

Project P04 builds on an established model of superficial pyoderma in dogs. The working hypothesis that canine pyoderma triggers specific biomarkers and AI-based video monitoring and thermography can refine the infection model by detecting pain- and itch-related behaviours and tissue inflammation.

The model will be used for:

• Local analysis using skin biopsies for histological and molecular examination
• Systemic analysis to conduct blood tests to detect broader physiological changes
• Develop lytic phage-based treatments targeting Staphylococcus pseudintermedius as alternatives to traditional antibiotics

P05 will investigate the hypothesis that Marek's Disease Virus (MDV) induces stress response markers, alters behaviour and agility in infected animals and that tumour cells can be identified in exfoliated mucosal cell (EMC) samples  

Research Goals include:

• Precisely determine the onset of MDV disease.
• Refine experimental procedures
• Reduce data variance and the number of animals used in infection studies

The long-term vision is to apply findings to improve early MDV detection in the poultry industry and as such contribute to reduce the suffering of millions of chickens.

Project P06 focuses on monitoring Hepatitis E Virus (HEV) progression using non-invasive methods. The aim is to assess stress and liver inflammation through salivary biomarkers, supported by AI-assisted behavioural analysis and thermal imaging.

Key points:

• Development of a non-invasive HEV scoring protocol
• Use of salivary biomarkers, AI, and thermal imaging
• Refinement of animal research with translational potential

    

Project P07 centrally supports the project groups of the 3RTG. It investigates stress biomarkers in host–pathogen infection models, focusing on glucocorticoid metabolism and its behavioural relevance. The project also explores novel biomarkers and epigenetic changes for improved disease tracking and model refinement.

Key points:

• Characterisation of glucocorticoid profiles via the HPA axis (metabolised in a species-specific but not yet fully explored manner)
• Identification of novel biomarkers and epigenetic changes
• Application in disease diagnosis, monitoring, and model refinement

    

Project P08 centrally supports the other groups by providing a methodological foundation for automated, AI-assisted behaviour analysis and thermography in order to analyse animal behaviour in infection models. This approach is expected to improve model refinement and enable better severity assessment by non-invasive methods.

Key points:

• AI-assisted behaviour analysis of video and thermal data
• Comparative study across multiple host species
• Identification of humane endpoints for severity assessment