Microbiomes and worker tasks

Highlighting the article written by J. C. Jones et al. in Insectes Sociaux

Written by Insectes Sociaux Editor-in-Chief, Michael Breed

Molecular techniques for identifying microbial community composition have created a
true biological revolution. Recent discoveries lead us to understand the bacteria as an
evolutionarily complex and diverse domain, and this in turn has sparked interest in
characterizing microbiota from a large number of contexts. Of particular significance has been the exploration of gut microbiomes, which vary dramatically among species, and developmentally within species. Gut microbiomes interact strongly with diet and health, giving added interest to studies focusing on this subset of communities (Dunn 2011, DeSalle and Perkins 2016).

We have long understood the importance of the gut microbiome in social insect species. In termites, some components of the microbiota reduce cellulose to usable sugars while in other species, members of the microbiota fix nitrogen. More recent studies of ant and bee gut microbiomes have shown some level of intraspecific consistency even over broad geographic ranges, but also variation associated with diet and to a certain extent differences among colonies.

In this issue of Insectes Sociaux, Jones and her colleagues (Jones et al 2018) focus on
differences in the gut microbiota based on task group in honeybee (Apis mellifera) colonies. This is a question previously addressed by Kapheim et al (2015) but Jones and colleagues add critical dimensions by age-matching the worker bees in their study and collecting gut samples from bees observed performing specific tasks.

Each of five experimental colonies consisted of 1500 workers of the same age and from
the same source colony (400 of which Jones and colleagues individually marked). They
observed worker behavior in ten to fourteen-day old bees. Nurses, food receivers/handlers and foragers were noted and collected. This approach allowed assessment of diet and task-related differences in microbiomes independent of age-related developmental effects.

Jones et al (2018) found that Firm-4 (Lactobacillus mellis), one of the characteristic
bacteria of the honeybee microbiome, was more prevalent in nurse and food handling bees than in foragers. This pattern was also seen with quite a few other bacteria species, which had higher presences in nurses and/or food handlers than in foragers. One species, Lactobacillus kunkeei, was more common in forager guts, although they found it less commonly there, so this result is more provisional. Of particular note in the guts of food processing bees was Bartonella apis, as this species expresses genes that may be involved in the degradation of secondary plant metabolites.

Globally, the microbiomes of nurses and food handlers were more diverse than the
microbiome of foragers. Jones et al (2018) suggest that the needs for carbohydrate metabolism are higher for nurses and food handlers and that perhaps this drives functional differences in the gut microbiome between these task groups and foragers.

Concerns over bee health, responses of bees to diseases or parasites, and the impact on bees of the agricultural use of antimicrobials have generated much of attention given to bee microbiomes (Napflin and Schmid-Hempel 2018, Raymann and Moran 2018). While these topics are important, the microbiomes of social insects existed long before humans started to impact social species, and social insect microbiomes must have evolved alongside sociality. How might gut microbiomes facilitate worker task performance? Do they determine workers’ roles within colonies? The cause and effect relationship between task group and microbiome could go in either direction, with task environment driving the microbiota or the nature of the microbiological community feeding back into the task choice of bees. This study presents these alternatives as tantalizing avenues to pursue in future research.


DeSalle R, Perkins SL (2016) Welcome to the microbiome: Getting to know the trillions of bacteria and other microbes in, on, and around you. Yale University Press 264pp.

Dunn R (2011) The wild life of our bodies: Predators, parasites, and partners that shape who we are today. Harper 304pp

Jones JC, Fruciano C, Marchant J, Hildebrand F, Forslund S, Bork P, Engel P, Hughes WOH (2018) The gut microbiome is associated with behavioural task in honey bees. Insect Soc https://doi.org/10.1007/s00040-018-0624-9

Kapheim, KM, Rao VD, Yeoman CJ, Wilson BA, White BA, Goldenfeld N, Robinson GE (2015) Caste-specific differences in hindgut microbial communities of honey bees (Apis mellifera). PLoS ONE 10: e0123911

Napflin K, Schmid-Hempel P (2018) Host effects on microbiota community assembly. J Anim Ecol 87: 331-340

Raymann K, Moran NA (2018) The role of the gut microbiome in health and disease of adult honey bee workers. Current Opinion in Insect Science 26: 97-104

Does size matter when using celestial cues to navigate towards home?

A blog post highlighting the article by R. Palavalli-Nettimi and A. Narendra in Insectes Sociaux

By Ravindra Palavalli-Nettimi and Ajay Narendra

Imagine finding a location in a new city without any map. How would you navigate toward your destination?

If you were an ant, you could use celestial cues such as the position of the sun or the polarised skylight pattern (Wehner and Strasser 1985; Zeil et al. 2014) as a compass to navigate in the direction of your destination (e.g., nest). The compound eye of an ant has a few special ommatidia that are sensitive to polarised skylight (light waves oscillating in one orientation). However, the eye size and also the total number of ommatidia in the ants’ eyes decrease with their body size. Some ants have close to 4,100 ommatidia (Gigantiops destructor) in their eyes while a miniature ant has a mere 20 ommatidia (Pheidole sp.). However, it is not clear how this variation affects their ability to navigate.



Size variation in ant heads.


In this study, we investigated how size variation affects ants’ ability to use celestial cues to navigate towards their nest.

To test this, we captured ants on their way to their nest and displaced them to a circular platform. The displacement site was at least 500-1,000 m from the ants’ nest and was surrounded by a creek. Thus, the ants had never foraged there and could not use landmark cues to navigate, but instead, they had to rely on celestial compass cues to walk towards their nest. We filmed the paths taken by the ants using a video camera and later digitized their head position frame by frame.

We found that having fewer ommatidia does not affect the ants’ ability to use celestial cues. The ants’ heading direction on the platform did not significantly differ from the fictive next direction. Since larger ants have greater strides and thus travel more distance for the same number of strides, we also analyzed their heading direction at a distance on the platform scaled to the body size of the ants.

We also found that the smaller ants were slower and had less-straight paths than the larger ants, even after controlling for differences in leg size (correlated with body size and head width) and stride length. This finding means that a reduced ability of the smaller ants to access celestial compass information results in a less straight path and reduced walking speed. However, the overall ability to initially orient towards the nest using a celestial compass is retained in miniature ants. Thus, while miniaturization in ants can affect their behavioral precision, it may not always lead to a loss of vital behavioral capability such as using celestial cues to navigate.



Paths and heading directions of various ants that differed in head width and ommatidia count.


In conclusion, finding a destination in a new city might be a lot easier if we were ants—of any size—and could use celestial cues!


Wehner R, Strasser S (1985) The POL area of the honey bee’s eye: behavioural evidence. Physiol Entomol10:337–349.

Zeil J, Ribi WA, Narendra A (2014) Polarisation vision in ants, bees, and wasps. In: G Horváth (ed) Polarized light and polarization vision in animal sciences, Springer, Heidelberg, pp 41–60.