Periodic Reporting for period 4 - EPIDEMICSonCHIP (EPIDEMICS in ant societies ON a CHIP)
Reporting period: 2022-10-01 to 2023-03-31
Infectious disease has been and still is a significant challenge, despite advances in medicine and public health. The more and the closer the social interactions between hosts, the easier pathogens can spread through a social group. Since the type and frequency of social interactions, as well as the disease susceptibility of individuals, are very diverse, epidemiological processes are extremely difficult to predict during their course, despite efforts such as contact tracing.
Social insects form very large colonies with intense social contacts. Studying their colonies allows full observation of the social interactions of all colony members, and determination how individual actions contribute to disease protection at the level of the individual and the whole colony. Social insects are hence a very good model system for the understanding of epidemics in social groups. In this project, we use ants to study how their individual hygiene behaviors synergize to prevent disease outbreaks in the colony.
Social insects form very large colonies with intense social contacts. Studying their colonies allows full observation of the social interactions of all colony members, and determination how individual actions contribute to disease protection at the level of the individual and the whole colony. Social insects are hence a very good model system for the understanding of epidemics in social groups. In this project, we use ants to study how their individual hygiene behaviors synergize to prevent disease outbreaks in the colony.
We studied how the collective phenomenon of colony-wide hygiene emerges from the actions of individual colony members, and which information the ants use to assess pathogen threat, like infective fungal spores on their body surface. We found that the ants’ grooming actions can be triggered by a single chemical component of fungal cells, which allows the ants to identify a fungal threat on affected colony members. The ants are further able to adjust their sanitary actions to disease threat-level, by use of simple rules combining the pathogen load they detect on others and the social feedback they receive from others. We also found that ant colonies have a high resilience to disease, being able to recover and to even pass on immunization through the colony, ensuring high fitness.
Using an insect model system that allows full surveillance and even manipulation of social interactions allows to see how individual actions affect the outcome of collective processes at the level of the group, respectively the whole system. Such knowledge informs epidemiological modelling will help to increase the predictability of epidemiological processes.