We experimentally manipulated two key aspects of colony composition, genetic structure and age structure, to generate replicate social networks predicted to differ in transmission risk. These experiments demonstrated that workers of different genotypes exhibit consistent behavioural differences that translate into measurable variation in network topology. Similarly, colonies composed of workers of different ages showed systematic differences in spatial organization and interaction patterns. In parallel, a peer-reviewed study (Jud et al., Proc. R. Soc. B) showed that colony genotype composition can shape behavioural dynamics and colony-level cycles, providing complementary evidence that collective organisation is predictable and experimentally tractable in O. biroi. To complement the empirical work, a computational pipeline was developed to simulate disease spread on temporal networks derived from automated behavioural tracking data.
To test whether individuals facing higher infection risk invest more in constitutive immune defences, we used O. biroi to decouple behavioural role from genotype and age. As a foundation, we annotated the immune gene repertoire of O. biroi from the genome by homology, identifying 256 candidate immune-related genes. We then combined fine-scale automated behavioural tracking with three complementary measures of baseline immune investment: immune-related gene expression quantified by transcriptomics, antibacterial activity measured in lysates, and survival following experimental pathogen exposure. Contrary to a long-standing hypothesis, we found no evidence that individuals engaging more strongly in high-exposure (forager-like) behaviours show higher constitutive immune investment; instead, baseline immune measures were largely uniform across behavioural phenotypes (see Li et al., 2025).
We also investigated how immune activation alters social organisation and the distribution of immune function within colonies. The core component of this work demonstrated that experimentally immune-challenged individuals occupy a more central position in the colony’s interaction network, rather than being avoided (Alciatore et al., 2021). This finding provided experimental evidence that immune status reshapes social networks in ways that are directly relevant for disease transmission.
Beyond this original objective, additional experiments testing immune priming revealed that prior exposure to live bacterial pathogens can enhance survival upon secondary exposure in O. biroi, and that this protection can be transmitted to nestmates. Additional experiments examined how bacterial infections affect social behaviour towards adults and larvae. To test predictions from network epidemiology by monitoring parasite transmission across experimental contact networks we established Diploscapter nematodes as a natural parasite system of ants and developed protocols for experimental infection.
Experiments combining behavioural tracking, infection assays, transcriptomics, and chemical analyses demonstrated that 1) Diploscapter parasitizes a specific gland in the ant head and affects host survival and physiology; 2) Differences in infection risk arise from behavioural variation alone: foragers become infected earlier and carry higher parasite loads than genetically identical nurses, and 3) Infection feeds back on social organization by reducing activity and increasing spatial overlap among colony members.
These results provide direct causal evidence that behavioural organization structures infection risk and that infection in turn reshapes social networks. The establishment of Diploscapter as an experimentally tractable parasite system represents a significant methodological advance for the study of transmission in ant societies.
The results of EPIDEMIC have been disseminated through several open-access, peer-reviewed publications and conference presentations, and further manuscripts are under preparation. Several events such as the Long Night of the Sciences were used to disseminate the findings to a lay public. The automated tracking infrastructure, new infection protocols developed during the project, and computational pipelines now form a durable experimental platform for future studies of epidemiology and other forms of biological transmission.
