Microbial associates and social behavior in ants

Socializing in an Infectious World: The Role of Parasites in Social Evolution of a Unique Rodent Family

Transmission of parasites between hosts is facilitated by close contact of hosts. Consequently, parasites have been proposed as an important constraint to the evolution of sociality accounting for its rarity. Despite the presumed costs associated with parasitism, the majority of species of African mole-rats (Family: Bathyergidae) are social. In fact, only the extremes of sociality (i.e., solitary and singular breeding) are represented in this subterranean rodent family. But how did bathyergids overcome the costs of parasitism? Parasite burden is a function of the exposure and susceptibility of a host to parasites. In this review I explore how living in sealed burrow systems and the group defenses that can be employed by closely related group members can effectively reduce the exposure and susceptibility of social bathyergids to parasites. Evidence suggests that this can be achieved largely by investment in relatively cheap and flexible behavioral rather than physiological defense mechanisms. This also shifts the selection pressure for parasites on successful transmission between group members rather than transmission between groups. In turn, this constrains the evolution of virulence and favors socially transmitted parasites (e.g., mites and lice) further reducing the costs of parasitism for social Bathyergidae. I conclude by highlighting directions for future research to evaluate the mechanisms proposed and to consider parasites as facilitators of social evolution not only in this rodent family but also other singular breeders.

Eusociality is linked to caste-specific differences in metabolism, immune system, and somatic maintenance-related processes in an ant species

The social organization of many primate, bird and rodent species and the role of individuals within that organization are associated with specific individual physiological traits. However, this association is perhaps most pronounced in eusocial insects (e.g., termites, ants). In such species, genetically close individuals show significant differences in behavior, physiology, and life expectancy. Studies addressing the metabolic changes according to the social role are still lacking. We aimed at understanding how sociality could influence essential molecular processes in a eusocial insect, the black garden ant (Lasius niger) where queens can live up to ten times longer than workers. Using mass spectrometry-based analysis, we explored the whole metabolome of queens, nest-workers and foraging workers. A former proteomics study done in the same species allowed us to compare the findings of both approaches. Confirming the former results at the proteome level, we showed that queens had fewer metabolites related to immunity. Contrary to our predictions, we did not find any metabolite linked to reproduction in queens. Among the workers, foragers had a metabolic signature reflecting a more stressful environment and a more highly stimulated immune system. We also found that nest-workers had more digestion-related metabolites. Hence, we showed that specific metabolic signatures match specific social roles. Besides, we identified metabolites differently expressed among behavioral castes and involved in nutrient sensing and longevity pathways (e.g., sirtuins, FOXO). The links between such molecular pathways and aging being found in an increasing number of taxa, our results confirm and strengthen their potential universality.

Integrating real-time data analysis into automatic tracking of social insects

Automatic video tracking has become a standard tool for investigating the social behaviour of insects. The recent integration of computer vision in tracking technologies will probably lead to fully automated behavioural pattern classification within the next few years. However, many current systems rely on offline data analysis and use computationally expensive techniques to track pre-recorded videos. To address this gap, we developed BACH (Behaviour Analysis maCHine), a software that performs video tracking of insect groups in real time. BACH uses object recognition via convolutional neural networks and identifies individually tagged insects via an existing matrix code recognition algorithm. We compared the tracking performances of BACH and a human observer (HO) across a series of short videos of ants moving in a two-dimensional arena. We found that BACH detected ant shapes only slightly worse than the HO. However, its matrix code-mediated identification of individual ants only attained human-comparable levels when ants moved relatively slowly, and fell when ants walked relatively fast. This happened because BACH had a relatively low efficiency in detecting matrix codes in blurry images of ants walking at high speeds. BACH needs to undergo hardware and software adjustments to overcome its present limits. Nevertheless, our study emphasizes the possibility of, and the need for, further integrating real-time data analysis into the study of animal behaviour. This will accelerate data generation, visualization and sharing, opening possibilities for conducting fully remote collaborative experiments.