During the first year of the project, we successfully accomplished the objectives set in two milestones: i) Milestone M1, at month M3, concerning the setup of dissemination channels (website, social media, etc.), the definition of the experimental methods, as well as of the plans for data management and dissemination/exploitation activities; ii) Milestone M2 at month 12, concerning the completion of the first set of experiments on the engineering of synthetic circuits for aggregation and swarming, the building of the environment for experimentation with real/virtual gradients, and the development of the first version of the ethics framework. During the second reporting period, we have successfully accomplished the majority of the objectives set in Milestones M3 (The design of mechanisms for aggregation, Prototyping of mechanisms for selective locomotion modulation and behavioural swicth response, The development of models of heterogeneous collective behaviours) and M4 (The design of all behavioural building blocks, Completion of the study focused on collective sensing, Completion of the study based on data driven models of BABots behaviour, The design of mechanisms for bio-containment). Nevertheless, some activities have been delayed due to problems emerged during the research work (i.e. Task T1.1 and Task 3.1),while other activities have been delayed due to the necessity to further explore unexpected phenomena or to further improve planned solutions (i.e. Task 2.2 and Task T4.2). In the following, I provide further details of the scientific work accomplished in the first and second reporting period.
As far as it concern the design of BABot behavioural building blocks (WP1), one line of work focused on engineering aggregation, enabling C. elegans worms to become collectively attracted to one another. To achieve this, we exploited attractive sex pheromones. Another line of work aims to change how worms move depending on what they feel around them. We introduced the chemical messenger serotonin into touch-sensitive neurons, so that physical contact can influence movement. The third direction is the most advanced and ambitious one. Its goal is to give BABots the ability to switch tasks depending on what they detect in their environment. In the future, this could allow them to respond to the invasion of a harmful bacterium in an agricultural environment, such as Serratia marcescens, by first locating a reserve of viruses that kill bacteria, and then transporting them to the infection site.
The team also introduced a new sensory pathway by adding an insect-derived receptor, called Orco, into the worms’ olfactory system. This allows the worms to respond to an artificial chemical cue that they would not normally detect. Combined with their natural attraction to bacterial odors, this creates the basis of a switchable system in which worms can be redirected from one target to another.
Finally, the biocontainment research has produced very encouraging results. The team has developed a two-layer containment strategy that achieves strict 100% sterility.
The animal behaviour team studies how BABots can act cooperatively and overcome the limits of individual worms. Their goal is to understand how groups sense their environment, move together, and eventually perform tasks more effectively as a collective than as isolated individuals. A first part of this work focused on building the experimental tools needed to study these behaviours in a controlled way. The team developed a specialised odour-flow chamber and virtual sensory environments that make it possible to expose worms to precisely controlled chemical cues. Another major line of work examined whether ordinary, unmodified C. elegans already show signs of collective sensing when moving toward chemical cues. In parallel, the researchers discovered a new type of collective behaviour in natural nematode populations: under stressful conditions, dozens of worms can self-organise into a living tower. This behaviour appears to help collective dispersal, and it offers a new way to study how groups of worms coordinate and share information. The team is now investigating whether this behaviour also involves a form of collective sensing. Finally, the project also examined mixed groups made of different worm strains to test whether some individuals can guide or influence the rest. In unmodified populations, no strong leadership effect was detected: each strain mostly kept its own intrinsic behaviour even when mixed with others.
The modelling team investigates the rules behind collective behaviour and aims to turn these insights into predictive tools for designing and controlling BABots. In practice, this means building models that connect what individual animals sense and do at the collective level. A first line of work uses experimental data from the genetics and animal behaviour teams to build data-driven models of BABot behaviour. A second line of work focused on more abstract population-level models to understand how differences between individuals can improve cooperation and collective performance. A third line of work connected these abstract ideas to more realistic simulations of moving agents. The team developed large-scale simulations of dense worm populations to reproduce patterns observed in experiments, including branching or arm-like collective structures.
The ethics team has been working to identifying and analysing the ethics questions relevant specifically to BABots. For any research project that deals with genetic engineering, intrinsic issues such as “playing God” and “unnaturalness” come up. We have been studying the extent to which Europeans find these issues troubling.
To conclude the BABot project, the consortium is developing a demonstrator that tests how engineered worm collectives respond to a controlled bacterial infection, synthesising all workpackage efforts. This demonstrator focuses on the pathogenic bacterium Serratia marcescens and evaluates whether BABots can detect the bacteria, move toward them, and help deliver bacteriophages, viruses that specifically infect and kill bacteria.
