Periodic Reporting for period 4 - DISEASE (Disease Risk And Immune Strategies In Social Insects)
Período documentado: 2022-09-01 hasta 2023-08-31
Group-living has been predicted to have opposing effects on disease risk and immune strategies. First, since repeated contacts between individuals facilitate pathogen transmission, sociality may favour high investment in personal immunity. Alternatively, because social animals can limit disease spread through collective sanitary actions (e.g. mutual grooming) or organisational features (e.g. division of the group’s social network into distinct subsets), sociality may instead favour low investment in personal immunity. The overall goal of this project is to experimentally test these conflicting predictions in ants using advanced data collection and analytical tools. I will first quantify the effect of social organisation on disease transmission using a combination of automated behavioural tracking, social network analysis, and empirical tracking of transmission markers (fluorescent beads). Experimental network manipulations and controlled disease seeding by a remote-controlled ant dummy will allow key predictions from network epidemiology to be tested, with broad implications for disease management strategies in other species. I will then study the effect of colony size on social network structure and disease transmission, and how this in turn affects investment in personal immunity. This will shed light on far-reaching hypotheses about the effect of group size on social organisation ('size-complexity’ hypothesis) and immune investment (‘density-dependent prophylaxis’). Finally, I will explore whether prolonged pathogen pressure induces colonies to reinforce the transmission-inhibiting aspects of their social organisation (e.g. colony fragmentation) or to invest more in personal immunity. This project will represent the first empirical investigation of the role of social organisation in disease risk management, and allow its importance to be compared with other immune strategies. It will significantly advance our understanding of the complex feedback between sociality and health, and uncover the ants’ optimal investment in disease defences depending on colony size, social complexity, and disease pressure.
During the first 30 months of the action, we have built 10 automated ant tracking systems and set-up all the equipment necessary for the projects. Furthermore, we have established new methodologies that are crucial to the success of the project. These include the development of a theoretical framework for engineering contact networks with particular statistical properties relevant for disease transmission; the development of a flow cytometry-based method for the simultaneous quantification of the transmission of multiple non-pathogenic agents through ant colonies; and the development of simple algorithms for the automated extraction of target behaviours such as grooming from the tracking data. Using these new methodologies, we have performed two large-scale tracking experiments. The first experiment aimed to investigate how nest architecture influences the social networks of ant colonies occupying those nests. The second experiment aimed to investigate how colony size influences social network topology, pathogen transmission risk and individual strategies to mitigate disease threat. In addition, we have started a third large-scale tracking experiment to investigate how previous experience with infectious pathogens influence which individuals undertake risky sanitary care. Finally, we have uncovered two simple individual-level movement mechanisms underlying the spatial segregation into well-separated worker task groups within nests of of social insects, which is known to play a major role in decreasing epidemic risk in insect societies.
Our work on the movement mechanisms underlying spatial segregation in nests of social insects made use of a new approach based on the analysis of complex ‘bipartite’ networks involving two different types of nodes (locations and individuals). This approach has the advantage of combining both the social and spatial structure of the colony within a single representation, thus providing an objective method for functional mapping of the nest into task zones and opening the way to new quantitative analyses of spatial organisation in animal groups. Furthermore, this work shows that the one of the most prominent features of organisational immunity likely emerges from exceedingly simple and apparently universal mechanistic origins.
The development of a general framework for the independent manipulation of network properties associated with disease transmission is a powerful tool and a significant achievement because network properties are highly correlated and are notoriously difficult to manipulate independently of one another. This will open the way to precise empirical testing of predictions from network epidemiology and help tease apart the role of different network properties on epidemic risk.
Data collection and analysis are still ongoing for the large-scale tracking experiments aimed at understanding the role of spatial organisation, group size and previous experience in disease risk management by ant colonies; we expect to shed new light on these aspects within the next 12 to 18 months.
The development of a general framework for the independent manipulation of network properties associated with disease transmission is a powerful tool and a significant achievement because network properties are highly correlated and are notoriously difficult to manipulate independently of one another. This will open the way to precise empirical testing of predictions from network epidemiology and help tease apart the role of different network properties on epidemic risk.
Data collection and analysis are still ongoing for the large-scale tracking experiments aimed at understanding the role of spatial organisation, group size and previous experience in disease risk management by ant colonies; we expect to shed new light on these aspects within the next 12 to 18 months.