Impact of the social environment in insect sensory systems

The origin and maintenance of division of labour in an Indian paper wasp

Division of labour (DoL) is of prime importance in the success of social insects in various ecosystems and benefits their colonies by increasing efficiency and productivity. This review summarizes more than three decades of experimental evidence collected towards understanding the emergence and maintenance of division of labour in the Indian tropical paper wasp Ropalidia marginata. This primitively eusocial species provides an interesting variation between newly founded colonies and mature colonies in terms of the behavioural mechanisms regulating division of labour. Newly founded colonies rely on physical dominance behaviour for establishing division of labour. Workers in mature post-emergence colonies continue to implement physical dominance as a way to regulate non-reproductive division of labour in a decentralized manner, while the queens switch to chemical regulation of worker reproduction. We discuss experiments that build evidence toward establishing R. marginata as an important model for understanding the origin and maintenance of division of labour.This article is part of the theme issue 'Division of labour as key driver of social evolution'.

Molecular Adjustment to a Social Niche: Brain Transcriptomes Reveal Divergent Influence of Social Environment on the Two Queen Morphs of the Ant Temnothorax rugatulus

Social insects form complex societies with division of labour between different female castes. In most species, a single queen heads the colony; in others, several queens share the task of reproduction. These different social organisations are often associated with distinct queen morphologies and life-history strategies and occur in different environments. In the ant Temnothorax rugatulus, queens are dimorphic. Macrogynes and microgynes reside in mono- and polygynous colonies and at lower and higher elevations, respectively. We analysed plastic changes in brain transcriptomes in response to the social environment in these queen morphs and their workers. We manipulated the number of queens over 4 months to investigate whether transcriptional activity is influenced by queen morph, social environment or their interaction. Changes in gene expression in the queens' brains in response to our manipulations were largely influenced by the interaction between social environment and queen morph, rather than independently by these factors. Macrogynes and microgynes thus adjust differently to their social environment. Similarly, worker transcriptomes were influenced by an interaction between behavioural type, that is, nurses or foragers, and queen morph. Nurses differentially regulated genes related to nutrition depending on queen morph, suggesting a link between social environment and metabolic dynamics in ant colonies. Overall, our study sheds light on how the social environment influences the molecular physiology of social insects. Furthermore, we demonstrate that in this ant with two queen morphs, worker physiology depends on queen morph and their role in the colony.

Neural correlates of individual facial recognition in a social wasp

Individual recognition is critical for social behavior across species. Whether recognition is mediated by circuits specialized for social information processing has been a matter of debate. Here we examine the neurobiological underpinning of individual visual facial recognition in Polistes fuscatus paper wasps. Front-facing images of conspecific wasps broadly increase activity across many brain regions relative to other stimuli. Notably, we identify a localized subpopulation of neurons in the protocerebrum which show specialized selectivity for front-facing wasp images, which we term wasp cells. These wasp cells encode information regarding the facial patterns, with ensemble activity correlating with facial identity. Wasp cells are strikingly analogous to face cells in primates, indicating that specialized circuits are likely an adaptive feature of neural architecture to support visual recognition.