Pathogens such as bacteria, viruses and parasites cause significant harm to animals and humans. Especially in veterinary medicine, many infectious diseases threaten animals that are kept as pets or serve as farm animals for food production. Research into infectious diseases relies heavily on animal models, as they provide important insights into the pathogenesis and immune responses and are of greatest significance in veterinary and human medicine. It is therefore the cornerstone in protecting animals and humans from various pathogens. Moreover, research using animal models often has a translational character, enabling findings to be applied across different animal species and to humans.

To date, most animal models used for infectious disease research cannot be replaced by alternative in vitro methods due to the systemic nature of the disease mechanisms. They are also of particular importance in deciphering immune responses or testing vaccines and anti-infective drugs. Although knowledge of infectious diseases has increased considerably over the last decades, the implementation of refinement measures in the animal models used has been neglected. In the 3RTG, we will employ the most common experimental host species (mice, chickens, pigs and dogs) and infection models well-established in our laboratories, including viral (Marek's disease virus, Theiler virus and Hepatitis virus E), bacterial (Listeria monocytogenes and Staphylococcus S. pseudintermedius) and parasitic (Heligmosomoides polygyrus and Giardia muris) infections.

Although it is well established that infected animals experience stress and exhibit altered behaviour, data on stress responses and behavioural changes remain limited. In the 3RTG, we aim to address the central hypothesis that infections elicit general stress responses and behavioural changes, which can be assessed at the metabolic level and through video-based observation combined with artificial intelligence analysis. Gaining new insights into these responses will enhance our understanding of the respective diseases while also contributing to the reduction of disease burden in experimental animals.

Our strategy enables the comparison of stress responses and behavioural data across different species and classes of pathogens, creating valuable synergies through the use of standardised methods. The interdisciplinary 3RTG graduate school will play a key role in training doctoral candidates at the forefront of infectious disease research, combining cutting-edge analytics with a strong emphasis on animal welfare in both experimental and farm animals.

This philosophy will be adopted in the comprehensive educational training programme of the doctoral researchers aligned with the 3R principles. This 3RTG aims to train and educate a new generation of young researchers being at the forefront of developing animal disease models and are highly qualified in all aspects of the 3Rs. A large demand exists for such qualified scientists who, in addition to conducting excellent research, will also promote and multiply the principle of the 3Rs.

Summary of the 3RTG Project

The 3RTG (Research Training Group) focuses on enhancing understanding of host/pathogen interactions across different representative animal species through the use of animal models. The key objective is to generate new scientific knowledge while applying the 3Rs principles (Replacement, Reduction, and Refinement) to improve animal welfare.

Objectives and Innovations:

• Investigate metabolic stress responses and behavioural changes in infected animals across multiple species (mice, chickens, pigs, dogs) and pathogens (viruses, bacteria, parasites).
• Utilise non-invasive techniques (e.g., thermography, saliva, faeces sampling) and AI-driven video analyses to monitor disease progression and stress responses.
• Establish a comprehensive, comparative database combining physiological, biochemical, and behavioural data to improve humane endpoints and reduce suffering.

Research Area I: Stress Response Analysis

• Infections trigger immune activation and stress, leading to metabolic, hormonal, and behavioural changes.
• Focus on identifying biomarkers (e.g., cortisol, cytokines, glucocorticoids) to monitor disease onset and progression.
• Emphasis on non-invasive sampling methods (e.g., saliva, faeces, hair) and analysis of novel stress indicators like sphingolipids and epigenetic markers
• Goal: Improve early disease detection, refine animal models, and contribute to therapeutic development.

Research Area II: Behavioural Analysis & AI-Assisted Monitoring

• Animals display species-specific behavioural changes during infection, currently insufficiently researched.
• Healthy behaviours will be characterised using video recordings and ethograms to be compared to disease behaviours.
• Behavioural data will be linked with physiological markers and used to refine experimental endpoints.
• A dedicated postdoctoral researcher, supporting all projects, will develop AI-based algorithms for long-term, automated behavioural analysis and thermography to detect early symptoms.
• AI tools are expected to enhance welfare, reduce mortality, and lower animal use by identifying pre-symptomatic behaviours.

Expected Outcomes:

• Creation of a joint, standardised database integrating stress and behavioural data across species and pathogens.
• Development of AI tools and biomarkers for early disease detection and humane experimental endpoints.
• Improved understanding of comparative pathophysiology and animal welfare, with broad applications in biomedical research and veterinary science.