EasyChair Preprint№ 1661

Ant microbial endosymbionts and the emergent
properties of social groups
Alessio Sclocco, Shirlyn Jia Yun Ong and Serafino Teseo

EasyChair preprints are intended for rapid
dissemination of research results and are
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October 14, 2019

Ant microbial endosymbionts and the emergent properties of social groups
Alessio Sclocco1, Shirlyn Jia Yun Ong2 and Serafino Teseo2†
1

Netherlands eScience Center, Amsterdam, The Netherlands(E-mail: a.sclocco@esciencecenter.nl)
2
School of Biological Sciences, Nanyang Technological University, Singapore(Tel: +65 63167088; E-mail: steseo@ntu.edu.sg)
Abstract: In the last fifteen years, research on animal models has provided advances on how gut symbiotic microbes
affect behavior and its underlying neurophysiology. However, most studies on the gut microbiota only take into exam
individual behavior without considering social dynamics. Contrarily, animals and humans live in complex societies where
they constantly adjust physiology and behavior to social interactions. To improve our understanding of how microbes andhosts interact and produce functional individual, social and collective phenotypes, we need to broaden our experimental
approaches to a group-level dimension. The ideal models for this purpose are social animals living in stable symbioses
with microbes, such as eusocial insects. In our research, we investigate Camponotus carpenter ants and their obligate
bacterial symbiont Blochmannia from a behavioral ecology perspective. We aim to create ant colonies including
differential proportions of bacteria-free individuals by suppressing Blochmannia with antibiotics. Then, using a machinelearning-based video tracking system, we will study network features and group-level behavior of such experimentalcolonies.
Keywords: Social Evolution; Microbiota-Gut-Brain Axis; Ants; Group-Level Behavior; Machine Learning; Real Time
Data Analysis

1. INTRODUCTION
In the last 15 years, the gut microbiota has been at thecenter of a scientific revolution. Correlations, but also
causal links have been established between gut microbe
activity and a plethora of aspects relevant to humanbiology and health. A key concept emerging from thislarge body of scientific work is the existence of anintimate relationship between gut microbes, the gut andthe brain, the microbiota-gut-brain axis [1]–[3].
According to this model, the complex communities ofbacteria living in the animal gut are in communication
with the gut itself and the brain through multiple channels.
These include the vagus nerve, the hypothalamicpituitary axis, neurotransmitters produced by the animal
body and the bacteria themselves, cytokines and otherbacterial metabolites. These connections constitute a
dynamic three-party system affecting animal
neurophysiology and the resulting behavioral output.
Little is known about how the relationship between themicrobiota-gut-brain axis of individual animals and theirsocial environment. This is surprising because, from abehavioral ecology perspective, the world of manygroup-living animals, including humans, is made ofmultiple complex social relationships. Social animals
need to iteratively adapt their behavior and underlying
physiology to their social environment. Inversely, eachindividual contributes to the social environment of its
partners, affecting their physiology and behavior throughsocial interactions. As gut microbes play a role indetermining individual behavior, they are also likely toaffect interindividual relationships within social groups.
Finally, through this influence on social interactions,microbes are predicted to ultimately affect the emergent
properties of social groups (Figure 1). Therefore, can we† Serafino Teseo is the presenter of this paper.

establish mechanistic links between symbiotic microbes
and behavior at social and group levels?

Figure 1. Predicted effects of gut microbes at different levelsof biological organization.

One way to explore this question is conducting
experimental research on animal models. However, thesemodel animals need to have three essential features: first,
they need to live in stable social groups; second, theymust establish permanent symbioses with gut
microorganisms; finally, they must be suitable forexperimental work on social and group-level behavior inlaboratory settings. The classic animal models of biology
do not always fulfill these conditions. For example,
Drosophila fruit flies are easy and inexpensive to rear,and very well characterized. Drosophila studies showthat commensal gut microbes affect physiological andbehavioral aspects, such as specific appetites for certain
foods [4], reproductive choices and mating [5]–[8], as
well as the recognition of related individuals [9].
However, fruit flies do not live in stable social groups andengage in little social interactions besides mating andfighting. Contrarily, mice and rats are relatively similarto humans from a social perspective, and have alreadybeen employed for a variety of behavior-relevant gut
microbiome studies [10], [11]. However, they havecomplex gut microbe communities, complex brains andrelatively high cognitive abilities, which complicatesexperimental approaches. Finally, to our knowledge there
is limited evidence for group-level cooperative behaviors
in mice and rats.
Eusocial insects like ants are instead good models toinvestigate how gut microbes are involved in social andgroup-level behavior. Their societies can be consideredas aggregations of simple cooperative modules(individual workers) acting for the benefit of the colony.
Interestingly, simple behavioral patterns of individual
ants produce extremely complex group-level phenotypes,
such as the nests of Atta leaf-cutter ants, or the living
bridges of Eciton army ants and Oecophylla weaver ants.
From a more practical perspective, and contrary forexample to fruit flies, ants perform working tasks andcommunicate with each other, which makes themsuitable for behavioral experiments in laboratory
conditions. Contrary to mice, ants have relatively simple
brains, as well as simple communities of symbiotic
bacteria [12], [13].

2. BACKGROUNDHYPOTHESISANDWORKING

Ant-associated microbes appear to be involved insocially relevant physiological dynamics. In particular,
several recent studies have investigated the relationshipbetween microbes and the colony-specific cuticularhydrocarbons of ants [14]–[18]. In our research, we aim
to explore this field further, with a special focus on
microbial influences during ant behavioral ontogeny.
The model system of our research is the association ofcarpenter ants of the genus Camponotus (familyFormicidae, subfamily Formicinae) and theirendosymbiont Blochmannia. Camponotus ants areamong the most successful ant genera in terms of species
number and global distribution, and most carpenter ant
species are easy to keep in laboratory conditions.
Blochmannia (γ-Proteobacteria) is a primary obligate
intracellular endosymbiont not only of Camponotus butof the whole ant tribe Camponotini [19], [20], which also
includes the genera Calomyrmex, Colobopsis,Dinomyrmex, Echinopla, Opisthopsis, Overbeckia andPolyrhachis.
Itisrelatedtofree-living
Enterobacteriaceae such as Escherichia coli and toseveral obligate insect intracellular endosymbionts suchas Baumannia, Sodalis and Wigglesworthia [21]–[23],[20]. Blochmannia’s most closely related bacteria appear
to be some facultative endosymbionts of mealybugs(order Hemiptera, family Pseudococcidae). This suggeststhat the ant-Blochmannia association may have emerged
through the nutritional symbiosis of a common ancestor
of Camponotini with sap-feeding insects [24].
Blochmannia is hosted in specialized cells(bacteriocytes) of the ant host internal midgut epithelium[25]–[27].
Interestingly, the 700 kb genome of Blochmannia [28]includes genes involved in nitrogen recycling and thesynthesis of amino acids such as tyrosine, tryptophan,leucine, isoleucine and valine [29], [30]. These aminoacids have potential behavior-relevant effects. For
example, tyrosine and tryptophan are precursors ofneurotransmitters such as dopamine and serotonin, which
directly affect individual neurophysiology. In addition,
dopamine also acts as a hormonal regulator in ants [31],which may as well affect individual and group-level
behavior. Finally, branched amino acids (leucine,isoleucine and valine), appear to be involved in thebiosynthesis of cuticular hydrocarbons [32], on whicheusocial insect nestmate recognition is based.
The abundance of Blochmannia varies throughout theant host life stages, and studies on Camponotus
floridanus show that Blochmannia titers are low in eggs
and larvae and increase significantly duringmetamorphosis, peaking in late pupation and early adultstages [29], [33]. Importantly, the life cycle phases inwhich Blochmannia peaks are also highly relevant for theant behavioral ontogeny. For example, in these phases,
ants develop their colony-specific blend of cuticularhydrocarbons and learn to discriminate nestmates fromnon-nestmates based on such blends [34].
Given that Blochmannia provides behavior-relevantmolecules in a sensitive time window for the ant hostbehavior, our working hypothesis is that behavioral
ontogeny in carpenter ants depends at least partially on
the action of its endosymbiont. We predict that longlasting effects on behavior (e.g., individual socialimpairment) could be produced via suppressing
Blochmannia in such critical phases.

3. METHODS
Ant workers are treated with antibiotics (Rifampicin)
either via feeding or via microinjections (Rifampicindissolved in 1x phosphate buffer saline (PBS)) using apressure injector connected to a pulled glass capillary(Figure 2). Treated and control workers are then mixed invarying proportions (0%, 33%, 66%, 100%) in 50individual experimental colonies. Each ant is marked
with a QR code glued on the thorax as an individual
identifier during experiments. The video tracking device
is constituted of ant-hosting units installed on an antivibration table, each with a single queenless experimental
ant colony. Each unit comprises a foraging area and a nest,
both isolated from external light and with 850 nm
infrared light-sensitive webcams placed on top. Nests areexposed to infrared light to collect images in darkness
conditions; foraging areas are exposed to visible and UVlight or infrared light in a 12h:12h LD alternation.
Webcams are connected to a computer where allprocessing takes place. Video streams are saved while atthe same time processed in real-time by the system. To
perform these operations, the system uses two highperformance Graphics Processing Units (GPUs).

4.
PERSPECTIVES:INTEGRATINGMACHINE LEARNING AND REAL TIMEDATA ANALYSIS IN ANT VIDEO TRACKING

Figure 2. a. A pulled glass capillary loaded with red fooddye used here to assess how injected liquid diffuses into theant hemolymph. b. Ice-anesthetized injected ants.

The processing software will consist of twosubsystems, one for tracking and the other for analysis.
Instead of relying exclusively on standard QR code
recognition, the tracking will be based on machinelearning. The use of machine learning will provide
resilience to partially invisible or damaged QR codes,and enrichment of the QR-based positional tracking withinformation on behavioral patterns. The analysis part willprocess the tracker output to produce real-time models of
the behavior of single individuals, as well as interaction
models of ant subgroups and of the colony as a whole.
We will first proceed by creating training and test sets
for the machine learning-based tracker. The training will
be constituted of videos of ants with QR codes, labeledwith the ID corresponding to the QR code itself; and ofvideos of the same individuals during social or individual
behaviors, qualitatively labeled according to the type.
The training set will then be employed to teach the
tracking system to recognize individual identity andbehavior, and the test set will be used to measure theaccuracy of the learned system.

5. CONCLUSIONSDisentangling the crosstalk of gut microbes, guts,
individual brains and societies is essential forunderstanding animal and human behavior, and may
ultimately contribute to create opportunities to treat
disorders such as depression and autism. Our researchaims to move steps in these directions by determining
how individual gut microbes influence and are influenced
by social dynamics.

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