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ABSTRACT Division of labor (DOL) is a characteristic trait of insect societies, where tasks are generally performed by specialized individuals. Inside workers focus on brood or nest care,

while others take risks by foraging outside. Theory proposes that workers have different thresholds to perform certain tasks when confronted with task-related stimuli, leading to

specialization and consequently DOL. Workers are presumed to vary in their response to task-related cues rather than in how they perceive such information. Here, we test the hypothesis that

DOL instead stems from workers varying in their efficiency to detect stimuli of specific tasks. We use transcriptomics to measure mRNA expression levels in the antennae and brain of nurses

and foragers of the ant _Temnothorax longispinosus_. We find seven times as many genes to be differentially expressed between behavioral phenotypes in the antennae compared to the brain.

Moreover, half of all odorant receptors are differentially expressed, with an overrepresentation of the 9-exon gene family upregulated in the antennae of nurses. Nurses and foragers thus

apparently differ in the perception of their olfactory environment and task-related signals. Our study supports the hypothesis that antennal sensory filters predispose workers to specialize

in specific tasks. SIMILAR CONTENT BEING VIEWED BY OTHERS DUFOUR’S GLAND ANALYSIS REVEALS CASTE AND PHYSIOLOGY SPECIFIC SIGNALS IN _BOMBUS IMPATIEN_S Article Open access 02 February 2021

MICROSTRUCTURES AT THE DISTAL TIP OF ANT CHEMOSENSORY SENSILLA Article Open access 11 November 2022 BUMBLE BEE QUEEN PHEROMONES ARE CONTEXT-DEPENDENT Article Open access 20 August 2021

INTRODUCTION Division of labor (DOL) is an important organizing principle of complex biological systems that arose independently during three of the major evolutionary transitions1. DOL was

originally formulated in the context of the production process in human societies2, but specialization to specific tasks is also found within cells and across many organisms1. Examples range

from bacteria, where clonal populations are divided into subpopulations focusing on different activities3,4,5,6 to multicellular organisms with differentiation of cells into different

tissues and organs, and individuals performing specific roles in animal societies7,8. To understand the evolution of complex life, it is therefore essential to investigate the mechanisms

that underlie DOL. DOL in insect societies results from individuals specializing in the performance of specific tasks. In addition to the reproductive DOL between fertile queens and

functionally sterile workers, there is a behavioral DOL among workers that specialize in tasks such as brood care, foraging, nest building, and defense9,10,11. Several factors can affect

task specialization, including age12,13, nutrition14,15, morphology16, genotype17,18,19, experience20, and colony size21,22,23. In leafcutter ant species, among others, behavioral

specialization of morphologically distinct groups of workers contributes to the DOL24. In most social insect species, younger workers tend to perform intranidal tasks, while older

individuals perform risky activities such as nest defense and foraging outside the nest25,26. Yet, such specialization among workers remains flexible, as foragers can revert to perform brood

care when needed27,28. Several molecular mechanisms have been implicated in the regulation of DOL. Task specialization is associated with transcriptional changes in the worker

brain29,30,31,32,33,34. Molecular pathways such as the insulin/insulin-like signaling (IIS), vitellogenin (Vg), and juvenile hormone (JH) pathways are involved in the regulation of worker

behavior35,36,37,38,39,40. Functional manipulations have confirmed that the expression of key genes in the worker brain controls task specialization41,42,43. Behavioral variation among

workers is also associated with signaling of biogenic amines (e.g., dopamine, octopamine, tyramine, serotonin), which act as neurotransmitters or neuromodulators involved in the modulation

of the responsiveness to task-associated stimuli44,45,46,47. Self-organization and collective behavior in insect societies are maintained via the exchange of chemical information48. Social

insects communicate primarily through glandular pheromones and complex mixtures of long-chain hydrocarbons on their cuticle. These cuticular hydrocarbons (CHC) facilitate recognition of

nestmates, developmental stages, castes, sexes, and species49,50. Social insects perceive chemical information via different types of sensilla in the antennae, small receptor organs embedded

in the integument that are connected to sensory neurons51,52,53. Decoding the identities of chemical compounds relies on odorant receptors (ORs) located within each sensillum54,55. ORs are

transmembrane proteins expressed in the dendrites of olfactory receptor neurons (ORN). The largely conserved OR coreceptor (_Orco_) of insects56 is required for odorant recognition in the

dendritic membrane: it forms an ion channel with specific OR, which determines the sensitivity and specificity of the ORN57. Odorant molecules penetrate through the antenna cuticular pores

and are transported by odorant-binding proteins to the ORN membrane, where they interact with receptors, leading to the generation of action potentials58,59. ORN axons relay signals from the

sensilla to the glomeruli of the antennal lobes in the insect brain, which are the first processing unit for olfactory information. Then, ORN make synaptic contact with the projection

neurons and local neurons, which transfer information to the central brain60,61,62. Several lines of evidence indicate that OR genes play central roles in the regulation of social life of

insects. First, social insect species typically harbor large numbers of OR genes63,64,65,66,67. Second, some OR gene families have specifically expanded during social evolution, such as the

9-exon subfamily in ants, which appears to serve an important function in the perception of CHC63,66,68,69,70,71. Third, species that evolved socially parasitic strategies resulting in

reduced behavioral repertoires show a strong and convergent reduction in the number of OR genes72. Finally, experimentally produced mutant ants that lack the _Orco_ gene (coding for the

co-receptor necessary for OR to properly function) show impaired social behavior73,74. Current DOL models bring together the chemical nature of social insect communication and variation

among workers in their response to chemical cues. They posit that flexible response thresholds to task-related chemical stimuli serve as regulators of worker specialization75. Workers take

on a particular task when the stimulus intensity exceeds their individual threshold for this task. Therefore, individuals with lower thresholds for a given task are more likely to perform it

than those with higher thresholds76. Individual response decisions and task performance are modulated via numerous parameters on different time scales7,77,78,79, and despite extensive

research on DOL and task allocation, these mechanisms are not fully understood. As the name suggests, response threshold models are based on an individual’s response to certain stimuli and

the variation in their responsiveness over time. However, these studies do not include in their models how these cues are processed65,79,80,81,82,83,84,85. The fact that the processing of

signal information has been primarily described in the insect brain (see ref. 86) may suggest that thresholds and associated responses are set in the central nervous system, possibly

regulated via molecular pathways in the brain that correlate with behavioral variation. We propose that DOL models would benefit from considering odor sensitivity as a potential upstream

sensory filter that may affect task specialization. Along these lines, we hypothesize that behavioral variation among workers may also stem from their ability and/or efficiency in detecting

different signals. For example, we propose that individuals that specialize in brood care do so because they are more sensitive to brood cues, rather than (or in addition to) being more

likely to respond to similar levels of brood cues. To test the hypothesis that a sensory filter regulates inter-individual behavioral variation, and thus the DOL in social insects, we

investigated transcriptional signals in the brain and antennae of workers that specialize in either brood care or foraging behavior in the ant _Temnothorax longispinosus_. We found that (i)

behavioral variation was associated with more extensive transcriptomic differences in the antennae than in the brain, (ii) these differences included a large proportion of the OR gene

repertoire, and (iii) individuals specializing in brood care overexpressed an OR gene family putatively involved in detecting social cues. These findings support our hypothesis that the

peripheral nervous system, acting as a sensory filter, plays an important role in regulating behavioral differences between workers and thus in the DOL of social insects. RESULTS

IDENTIFICATION OF _TEMNOTHORAX LONGISPINOSUS_ BEHAVIORAL PHENOTYPES Task specialization in the ant _T. longispinosus_ is neither genetically fixed nor rigid, but can change with age and in

response to colony needs39. We conducted behavioral observations of seven _T. longispinosus_ laboratory colonies to identify individuals that specialize in brood care behavior (hereafter

referred to as nurses), and others that specialize in foraging (hereafter referred to as foragers) (Fig. 1A; see “Methods” section for more details). The grouping of workers into the two

behavioral categories was based on the frequency of their location inside or outside the colony and on their behavior, especially whether they showed brood care or foraging behavior (Dataset

 S1). Individuals identified as nurses interacted with the brood in 54% ± 22% (mean ± sd) of the observations, and were recorded outside the nest in 1% ± 3% of the observations. On the

contrary, foragers were found outside the nest in 42% ± 26% of the observations but interacted with the brood in only 2% ± 4% of the observations. LARGER TASK-ASSOCIATED TRANSCRIPTOMIC

CHANGES IN THE ANTENNAE THAN IN THE BRAIN To investigate transcriptomic variation between nurses and foragers, we used RNA-seq to generate seven nurse and seven forager brain and antenna

samples, each consisting of pooled tissue from seven workers of a single colony. Of the 14,837 genes annotated in the _T. longispinosus_ genome, we found 91% (13,494) and 92% (13,683) to be

expressed (FPKM > 0) in the brain and the antennae, respectively. To investigate gene expression differences between nurses and foragers, we compared full models that included task as an

explanatory variable to reduced models that did not using the likelihood ratio test (LRT) method implemented in DEseq2. The influence of colony identity was controlled for by including it as

an explanatory variable in both full and reduced models. A Benjamini–Hochberg adjusted _p_ value of 0.05 was set as a threshold to obtain genes whose variation was significantly explained

by behavioral specialization in each tissue. We detected 339 differentially expressed genes (DEGs) in the brain (223 upregulated in nurses, 116 in foragers), and 2267 in the antennae (1241

upregulated in nurses, 1026 in foragers; Dataset S2 and Fig. 1B). We found an overlap of 162 DEGs between the two tissues, including 143 DEGs that showed differences in the same direction

across tissues. Principal component analyses (PCA) for both brain and antenna data reveal that most samples clustered by behavioral phenotype rather than colony of origin (Fig. 1C, D). OR

GENE EXPRESSION DIFFERS BETWEEN ANTENNAE OF NURSES AND FORAGERS To investigate whether odorant perception differs between nurses and foragers, we focused our attention on the expression of

OR genes in the antennae. We found that all 419 previously annotated OR genes in the genome of _T. longispinosus_72 were expressed in the antennae, and that 50% (209/419) of them were

differentially expressed between nurses and foragers. Specifically, 64 OR genes were upregulated in nurses (15% of all OR genes), and 145 in foragers (35% of all ORs) (Fig. 2). Then, we

studied which OR subfamilies were preferentially expressed in nurses and foragers. The 64 OR genes overexpressed in nurses belonged to three OR subfamilies, while the 145 OR genes

upregulated in foragers were distributed among 19 OR subfamilies. Foragers overexpressed 27, 19, 8, and 8 OR genes from the L, V, P, and H subfamilies, respectively, while no OR genes from

these subfamilies were upregulated in nurses (Dataset S3). We found that 63% (27/43) of the genes from the L subfamily and 73% (8/11) from the P subfamily were overexpressed in foragers,

which represents a significant overrepresentations (L subfamily: Fisher’s test, odds ratio = 3.67, _p_ value < 0.001; P subfamily: Fisher’s test, odds ratio = 5.25, _p_ value < 0.02).

For the V and H subfamilies we did not find such an overrepresentation, likely due to lower gene numbers (V subfamily: Fisher’s test, odds ratio = 1.64, _p_ value = 0.17; H subfamily:

Fisher’s test, odds ratio = 1.71, _p_ value = 0.30). On the other hand, we found that 80% (51/64) of the OR genes overexpressed in nurses belong to the 9-exon subfamily. This results in an

overrepresentation of the 9-exon subfamily in genes that were overexpressed in nurses (Fisher’s test, odds ratio = 22.18, _p_ value < 0.001), with 45% (51/114) of this subfamily being

overexpressed in nurses. In contrast, only 6% (8/137) of the 9-exon subfamily was overexpressed in foragers, which is less than expected by chance (Fisher’s test, odds ratio = 0.09, _p_

value < 0.001). We also found that nurses overexpressed _Orco_ compared to foragers (FDR _p_ value = 0.001). GENES IN BIOGENIC AMINE PATHWAYS VARY IN EXPRESSION BETWEEN NURSES AND

FORAGERS Biogenic amines have been implicated in the regulation of behavior, and they may affect sensory perception46,87,88,89,90. We therefore screened our lists of brain and antennal DEGs

for biogenic amine pathway genes. We detected five differentially expressed genes in the antennae that are associated with biogenic amine signaling. Genes in the serotonin

(_5-hydroxytryptamine_, DBV15_11483), tyramine (_tyramine beta-hydroxylase_, DBV15_00422) and octopamine (_octopamine receptor_, LOC112465659) pathways were upregulated in the antennae of

foragers, while nurses showed a higher expression of genes in dopamine (_dopamine 1-like receptor 2_, DBV15_07611) and octopamine (_octopamine beta2 receptor_, DBV15_10418) pathways (Fig. 

3A–E). These five genes were also expressed in the brain, but not differentially expressed between nurses and foragers. Also, no other biogenic amine pathway genes were found to be

differentially expressed in the brain. ASSOCIATION BETWEEN BEHAVIORAL VARIATION AND MOLECULAR PATHWAYS IN BRAIN AND ANTENNAE Our analysis revealed expression differences of genes expressed

in the brains of nurses and foragers involved in the regulation of task specialization in social insects. Previous studies have found that _Vg_ genes and the associated JH and IIS/TOR

pathways are important endocrine networks that play central roles in the regulation of lifespan, fertility and behavior in bees and ants36,91,92,93,94,95,96. Therefore, we searched and found

evidence in our RNA-seq data for task-associated expression of genes involved in the metabolism, biosynthesis, and regulation of these pathways in the brain and antennae (Table S1). These

genes included _conventional Vg_ (LOC112466671), _Vg-like A_ (named/classified as per;43 DBV15_03138), _venom carboxylesterase-6-like_ (DBV15_11528), and _protein takeout_ (DBV15_08771)

overexpressed in the brain of nurses. Meanwhile, _allatostatin A-like_ (LOC112454443) and _insulin-like growth factor I_ (_IGF1_) (LOC112454447) were found overexpressed in the brain of

foragers. Remarkably, _venom carboxylesterase-6-like_ and _IGF1_ were overexpressed in the antennae of nurses and foragers respectively. Additionally, high expression levels of the

zinc-finger transcription factor _Krüppel homolog-1_ (_Kr-h1_) were detected in the antennae of foragers (DBV15_06330) (Fig. 3F). The expression of this gene has been correlated with caste

and behavioral differences in the brain of social insects93,97,98,99,100, but little is known about its function and gene targets in the antennae. We performed a GO enrichment analysis to

gain a deeper understanding of the biological processes represented in the lists of DEGs. This analysis detected many enrichments based on single one or few genes, and we mention below a few

interesting processes with the number of genes driving the enrichment in parentheses (see Table S2 for complete list). Genes that were upregulated in the brain of nurses were enriched for

biological processes such as _translation_ (19 genes), _cellular iron ion homeostasis_ (2 genes), and _catabolic process_ (6 genes); while _translation_ (22 genes), _endocytosis_ (6 genes),

_glucose metabolic process_ (4 genes), and _regulation of cell cycle_ (3 genes) were enriched in the antennae. In the list of genes that were overexpressed in the brain of foragers, we found

that enriched processes included _peptide metabolic process_ (4 genes), _methionyl-tRNA aminoacylation_ (1 gene), _positive regulation of type I interferon production_ (1 gene), and _cell

redox homeostasis_ (1 gene); while _phosphatidylinositol phosphorylation_ (4 genes), _inositol phosphate dephosphorylation_ (3 genes), _carbohydrate metabolic process_ (17 genes), _innate

immune response_ (2 genes), and _nucleotide catabolic process_ (3 genes) were enriched in the antennae. DISCUSSION In this study, we found evidence supporting the hypothesis that variation

among social insect workers in their ability to perceive different chemical signals could contribute to the regulation of task allocation, and thus to DOL in insect societies. To do so, we

analyzed brain and antenna transcriptomes of nurses and foragers of the ant _T. longispinosus_. We report several lines of evidence that support our hypothesis. First, we found almost seven

times as many genes to be differentially expressed between nurses and foragers in the antennae as in the brain, indicating that peripheral sensory organs may have an important function in

the task specialization process of social insect workers. Second, we found that half of all OR genes of the _T. longispinosus_ genomes are differentially expressed between the antennae of

nurses and foragers, suggesting that behavioral specialization is associated with different sensory filters that result in specific perceptions of the chemical environment. Third, our

analyses revealed that nurses and foragers upregulated distinct families of OR genes, indicating that their sensory filters may target different types of chemical cues, possibly adjusted to

the tasks they perform. Finally, we detected several genes in multiple biogenic pathways to be differentially expressed between the antennae of nurses and foragers, potentially involved in

fine-tuning the sensitivity of the odorant filters. Many organisms have evolved sensory filters to focus on only a subset of all environmental cues101,102,103,104. In insects, the peripheral

olfactory filtering system enables individuals to detect and discriminate odors that convey ecologically relevant information used to mediate important behaviors such as courtship,

locomotion and navigation to avoid predators and locate food or nesting sites105. For example, the mosquito _Anopheles gambiae_ strongly responds to odorant components of its vertebrate

hosts that provide meals106. Sensory filters have been selected for because they limit the amount of information perceived by the organism, and thus the energy and time required by the brain

to process it105. Within insect colonies, individuals typically exhibit many morphological and physiological traits associated with increased efficiency in task specialization. These can be

understood as adaptations that allow individuals to become more proficient at their task due to learning, training, or the perception of valuable task-related information, allowing the

colony to avoid the cost of task switching107. In this context, it is interesting to find that _T. longispinosus_ workers may have different sensory filters that would serve as a basis for

their task specialization, as workers would mostly perceive chemical cues that pertain to their tasks. Our findings indicate that the sensory filter of ant workers is dynamic, and its

changes may underlie their behavioral maturation. In this study, we report a higher number of DEGs between nurses and foragers in the antennae than in the brain. The brain is a heterogeneous

tissue in which different cell types perform very specific functions, which differ greatly in their gene expression108,109,110. Therefore, using the whole brain for transcriptome analyses

could make it more difficult to identify genes that are differentially expressed only in specialized parts of the brains of nurses or foragers. In comparison, the antennae might have a more

uniform cell composition, which could facilitate the identification of DEGs. In contrast to this prediction, a transcriptome comparison of two different behavioral phenotypes of worker honey

bees revealed that transcriptional differences are much more pronounced in the antenna than in the separately studied brain parts including the mushroom body, antennal lobe and central

brain111. Furthermore, Chandra et al.112. used whole-brain RNA-seq in several ant species to detect differential expression of the gene _Ilp2_ between castes, a gene that was later found to

be expressed in only about 15 cells of the pars intercerebralis. This led us to conclude that it may be slightly more difficult to identify DEGs in the brain than in the antennae, but this

unlikely explains the nearly seven-fold difference in the number of DEGs. Age, genetic background, social environment, individual experiences and hormones influence behavioral differences

between workers leading to DOL13,20,23,113,114,115. In our study, we expect that age differed between individuals identified as nurses and those identified as foragers, although we did not

measure it directly. However, we know from previous studies on _T. longispinosus_ that workers live between one to three years and switch from brood carer to forager about one year after

eclosion, when new generation of workers emerged and taken over the care of the brood43,116. Previous experiments designed to disentangle gene expression associated with behavioral

specialization, age and fertility showed that behavioral specialization is much more strongly associated with gene expression than age and fertility in _T. longispinosus_39. We propose that

the molecular and physiological regulators such as JH, Vg, biogenic amines, and nutritional status known to regulate task specialization could drive different OR expression patterns, which

in turn would produce behavioral variation via contrasting abilities to detect different sets of odors. This hypothesis is supported by several studies (reviewed in ref. 117) showing that

the physiological condition of an animal can influence the level of receptor expression, including mating status, oviposition, feeding, circadian rhythm, experience, and aging.

Alternatively, we cannot exclude that the exposure to different odors that is associated with performing different tasks may at least in part have affected OR gene expression in the

antennae. However, such an effect is unlikely to explain the large-scale variation in gene expression, as there is very limited evidence that the mere exposure to odors influences the

expression of the gene coding for the OR that binds this odor118,119. According to our sensory filter hypothesis, ant workers would be expected to primarily detect chemical cues that

correspond to their tasks. We found that the 9-exon subfamily of OR was overrepresented in genes that were upregulated in the antennae of nurses. Interestingly, recent studies have shown a

rapid expansion of the 9-exon subfamily in ants, and several lines of evidence indicate that OR genes from this subfamily mediate complex social interactions in ant colonies67,68,69,70.

First, comparisons of antennal transcriptomes revealed that 9-exon OR genes are expressed more frequently in workers than in males, suggesting a role in social communication among

workers63,70. Second, representative OR from the 9-exon subfamily can detect CHC extracts from several castes71. According to McKenzie et al.70, 9-exon OR genes were first expressed in

solitary ancestors of aculeate wasps and facilitated CHC discrimination, likely for prey or mate recognition, with a lineage giving rise to the ancestors of ants. Moreover, OR genes of the

9-exon subfamily were convergently lost in socially parasitic ant species that lost the ability to perform brood care or foraging72, suggesting that they are essential for the performance of

these worker tasks. Our finding of an overexpression of 9-exon OR genes in the antennae of nurses is in line with these previous studies, and suggests that many of these receptors have

important functions within the nest, such as sensing chemical cues from the larvae, queen, or other workers, and/or that they are less important for sensing task-related stimuli or other

signals outside the nest. Among the OR genes overexpressed in nurses was also the co-receptor _Orco_, which is widely expressed in olfactory sensory neurons and nearly unchanged in sequence

in distant insect taxa120,121,122. ORs form a unique class of heteromeric cation channels composed of two related heptahelical subunits: a divergent OR subunit that confers odor specificity,

and the co-receptor _Orco_ subunit123,124. Since those functional receptors would increase the sensitivity of the workers to odors, we propose that the overexpression of _Orco_ may indicate

higher olfactory sensitivity to odors in the antennae of nurses compared to foragers. This would be supported by previous studies that showed that changes in _Orco_ expression can be

indicative of physiological conditions and sensory receptivity125,126. The behavioral transition from nursing to foraging may be triggered by a lower efficiency in detecting brood cues via

the downregulation of specific OR genes (e.g., from the 9-exon subfamily). This would result in ants moving farther away from the brood, and this change in spatial location may trigger the

behavioral transition to outside tasks127,128. In addition to being less efficient at detecting brood cues, the sensory filter of foragers may also become fine-tuned to detect a more diverse

set of odors. Foragers overexpressed a greater number of OR gene subfamilies compared to nurses (19 and 3 for foragers and nurses, respectively), which may indicate that the olfactory

system of foragers could perceive the more diverse chemical environment outside the nest. Similar to the 9-exon subfamily, the L subfamily has also been expanded in social insects64,66,67,

and along with the P and H subfamilies, it has been lost in socially parasitic ants72,129. Interestingly, the OR genes from the L, P, V, and H subfamilies have been upregulated in foragers,

and thus may have a task-specific function, such as recognition of chemical cues related to environmental perception or recruitment cues outside the nest. OR genes belonging to subfamilies

L, H and V have been shown to be highly responsive to long-chain hydrocarbons and are overexpressed in the antennae of males and workers of the ant _Harpegnathos saltator_130. In addition,

several ORs of the H subfamily have been proposed to act as putative floral odorant detectors in the antennae of honey bees131. Finding task-specific variation in OR gene expression raises

the question as to which molecular mechanisms regulate those changes. Variation in biogenic amines levels have been identified as one of the leading causes of behavioral plasticity and

specialization of social insects to different tasks (reviewed in ref. 132). Functional manipulation of biogenic amines has led to changes in behavior, dominance status and reproductive

activity, as well as shifts in worker task performance133,134,135,136. Previous studies on insects revealed that olfaction-guided behavior is mediated by biogenic amine receptors in the

antenna, and their expression is involved in fine-tuning the sensitivity of the olfactory system89,117. Signal transduction of biogenic amine receptors is mediated by G protein-coupled

receptors (GPCRs) located on the cell membrane, which trigger different signaling cascades that lead to increased or decreased cAMP level and Ca2+ release137,138,139,140. For example,

modified concentration cAMP and intracellular Ca2+ levels due to octopamine-induced signal transduction in the moth _Manduca sexta_141 activate _Orco_, leading to changes in ORN

sensitivity142,143. Our results suggest that the biogenic amine signaling pathway may modulate the sensory filtering function of insect antennae and alter sensitivity to various signals. We

found that genes encoding tyramine and its precursor, octopamine, are upregulated in forager antennae, similar to genes involved in serotonin signaling. Tyramine and dopamine (which was

upregulated in nurses) have been implicated in modulating taste and olfactory receptor neurons, while serotonin may serve as a neurotransmitter and neurohormone in antennal vessels and

mechanosensory organs89. Serotonin influences foraging activity88 and regulates food intake in many animals144,145,146. Dopamine signaling also plays an important role in controlling the

insect circadian clock and mediating clock-controlled behavioral phenotypes such as locomotion147,148. In our focal species _T. longispinosus_, inside workers were found to exhibit a

stronger circadian rhythmicity than foragers, which may be regulated via differences in the acetylation of histone proteins149. Changes in behavior and olfactory sensitivity in insects could

be related to the expression of genes involved in IIS, target of rapamycin (TOR), JH and Vg pathways, according to age, circadian rhythm, mating and feeding status117. For example, appetite

state in _D. melanogaster_ is signaled by insulin, which upregulates a peptide receptor on the olfactory receptor cells that innervate the DM1 glomerulus. Activation of the DM1 glomerulus

is enough to drive the fly to reach for food150. Recent studies have shown that pheromone release and odor sensitivity appear to be under JH control in _Schistocerca gregaria_ and _Locusta

migratoria_, which could lead to behavioral changes151,152,153,154,155. Finally, an experimental downregulation of _Vg-like A_ in _T. longispinosus_ workers resulted in decreased brood care

behavior and a lower sensitivity to brood-related chemical cues, suggesting changes in odor perception and olfactory-driven decision making43. Our results reveal that genes associated with

all these pathways were differentially expressed in the brain and antennae between nurses and foragers, predicting a link between their role in task-associated behavioral changes and the

regulation of odor perception. Given the central role of IIS, Vg, JH, and TOR pathways in regulating division of labor in social insects, and our finding of task-associated patterns of the

antennal expression of genes from multiple biogenic amines, we hypothesize that these modulators and hormones could be involved in the regulation of the olfactory filter. How the detailed

molecular mechanisms of these pathways in the brain are causally linked to the complex changes in olfactory perception in the antennae should therefore be investigated next. CONCLUSION Our

transcriptomic analyses of the brain and antennae of _T. longispinosus_ nurses and foragers provide support to our hypothesis that behavioral variation and task specialization in ant workers

are regulated via differences in olfactory perception. We predict that antennal physiology acts as sensory filters that limit the type and amount of chemical information passed to the

brain. This would allow workers to target relevant chemical information from the environment and discriminate signal from noise without using energetically costly processing by the central

nervous system. We argue that this sensory filter is flexible and regulated through changes in physiological conditions such as age, nutrition, and hormones. Variation among workers in their

efficiency to detect specific chemical cues would result in task specialization and division of labor. The information perceived by the peripheral ORs is transmitted to the primary brain

center of the olfactory pathway, the glomeruli of the antennal lobes. The question now arises whether there are differences between nurses and foragers in the morphology or physiology of the

antennal lobes. A limited subset of active ORs and glomeruli might be easier to process and less energy consuming. Our study opens novel avenues of research to better understand the role of

sensory filters in controlling DOL in insect societies. METHODS SAMPLE COLLECTION AND BEHAVIORAL DETERMINATION A total of seven colonies of the ant _T. longispinosus_ were selected with an

average colony size of 110 ± 31.5 workers (mean ± sd, Dataset S4) at the moment when the workers were sampled. The ants were collected in the forests of the Edmund Niles Huyck Preserve,

Renssellearville, NY, USA (42°31′41.0′′N 74°09′38.8′′W), in June of 2018 with permission. Upon collection, we housed each colony in a plaster-floored nesting box (43 cm × 28 cm × 10 cm)

divided into three chambers containing a single slide nest, in which the colony relocated. A slide nest is an artificial nesting site comprised of a small Plexiglas cavity sandwiched between

two glass microscope slides. Colonies were established at the Johannes Gutenberg University in Mainz, Germany, under a 14 h:10 h light:dark photoperiod at 18 °C to a 22 °C temperature. We

provided honey and water ad libitum and fed crickets to the colony twice a week. To allow for visible behavioral division of labor between workers of the two behavioral phenotypes, we

marked, observed and recaptured ants from inside and outside the nest. We defined foragers as workers that perform outside-nest tasks, including gathering and searching for food and water

and exploring the environment surrounding the nest, while nurses remained inside the dark nest and cared for the ant brood. A total of 69 workers inside (from the brood pile) and 76 workers

outside the nest were marked with fine colored metal wires (0.02 mm Elektrisola, Eckenhagen, Germany). To immobilize the workers, they were placed with their heads and part of the thorax in

a notch of a soft sponge without prior anesthesia. Then we marked the ants with a very thin loop around the petiole. It was then checked that the wires did not interfere with the ants’

movement. We performed behavioral observations every 2 h, four times a day for 5 days (total = 20 scans), in which we noted down how many times an individual performed brood care and

foraging behavior and the position in the nest (Table S3). Based on these behavioral observations, the marked individuals found outside the nest, exploring the surroundings for food or

water, were identified as foragers. These workers usually do not care for the brood and do not frequently reside on brood piles, as ant colonies organize themselves spatially in a way that

reduces contact between foragers and brood156. We identified nurses as workers that remain inside the nest in direct contact with brood and were unlikely to leave the nest. Foragers were

found in 42% ± 26% of the observations outside of the nest, whereas nurses spend only 1% ± 3% outside. In contrast, nurses were interacting with the brood in 54% ± 22% of the observations,

whereas we found that foragers only did this only in 2% ± 4% of the observations. We scanned the behavior of workers over 20 observations, albeit earlier studies have shown that a single

observation makes it possible to group _T. longispinosus_ and other ants reliably into nurses and foragers that differ in behavior116,156, gene expression39 and CHC composition43.

Furthermore, spatial location can alone can predict behavior in _Temnothorax_ workers157. We focused in this study on individuals highly specialized on either foraging or brood care. Workers

that performed both tasks regularly were not included in this study. After all observations were completed, the marked nurses and foragers were collected, directly frozen in liquid nitrogen

and stored at -80 °C until further processing for dissection and pooling according to behavioral state and colony. RNA EXTRACTION AND SEQUENCING For RNA extraction, we removed both antennae

and stored them in a 1.5 ml Eppendorf tube containing 50 μl TRIzol (Invitrogen), cut the head off and fixed it on a slide with melted dental wax. We then made an incision around the head

with a surgical scalpel and removed the head capsule with forceps to expose the intact brain. Finally, we carefully pulled the brain out of the head capsule and removed the remains of other

tissues that were connected to it. The dissected brain was transferred to a 1.5 ml Eppendorf tube containing 20 μl PBS. Each dissection was completed in less than 5 min to prevent RNA

degradation. We dissected brain and antennae tissues from 48 nurses and 49 foragers. We pooled the brains and antennae from seven workers from each behavioral state and colony. The only

exception was the “GO” colony (NY18 E110), for which we pooled only 6 brains and 12 antennae from 6 nurses (Dataset S4) due to the loss of one sample during the dissection process.

Immediately after dissection of each brain and antennae, the Eppendorf tubes were kept on dry ice while we dissected the remaining individuals. Brain and antennae tissues were homogenized

with a pestle. Sample brains were transferred separately to a 1.5 ml Eppendorf tube containing 50 μl of TRIzol. We added 50 μl chloroform to each brain and antenna samples, gently inverted

for 30 s and then centrifuged samples at 12,000 × _g_ for 15 min at 4 °C. We collected the resulting supernatant and precipitated RNA with 25 μl 70% ethanol. We conducted the subsequent RNA

extraction with the RNeasy Mini Kit (Qiagen), following the manufacturer’s instruction. The resulting 28 samples (14 brains and 14 antennae) were stored at −80 °C until library preparation.

RNA-seq libraries were prepared by Novogene Company Limited, Cambridge, UK, using the NEBNext Ultra RNA Library Prep Kit for Illumina according to the manufacturer’s protocol. After

amplification and purification, 28 libraries were sequenced on an Illumina NovaSeq 6000 S4 flow cell platform using a paired-end 150 bp. Approximately 43 million raw reads were generated

from each library (Dataset S4). GENE EXPRESSION ANALYSES Raw data obtained from Novogene were checked using FastQC v.0.11.9158, and Illumina adapters were removed using Trimmomatic

v.0.36159. The protein-coding genes of _T. longispinosus_ together with the manual OR annotations (GCA_004794745.1)160; and the congener _T. curvispinosus_ (GCA_003070985.1) were retrieved

from the NCBI database and we used Liftoff v.1.6.1 tool161 to assign these annotations to the recently published _T. longispinosus_ genome72. In total, 10,029 of 13,061 (~77%) annotated

protein-coding genes were assigned from the original _T. longispinosus_ assembly (genes identified as “DBV15”) and 4808 were assigned from _T. curvispinosus_ (genes identified as “LOC”), for

a total of 14,837. For gene expression analysis, reads were mapped to our _T. longispinosus_ genome assembly, and the read counts table was generated using STAR 2.7.0162 with default

settings. Detailed mapping statistics for each sample is available in Dataset S4. We used the deseq2 v1.16.1 package for R to identify differentially expressed genes163. To avoid biased

results due to low read counts, we removed from the counting matrix those genes for which less than 10 of the reads mapped to at least 6 of our 14 samples (_n_ − 1 of the smallest sample

size). Then, we conducted a differential gene expression analysis with DESeq2164. We began with comparisons between nurses and foragers using the ~Colony+Task model, followed by a likelihood

ratio test (LRT) approach, with colony ID as a fixed factor. Genes were considered differentially expressed if the false discovery rate (FDR), using Benjamini–Hochberg procedure, had an

adjusted _p_ value of ≤0.05. The resulting lists of DEGs refer to genes that are overexpressed and underexpressed in foragers compared to nurses. We used the online tool Venny v.2.1

(https://bioinfogp.cnb.csic.es/tools/venny) to generate a Venn diagram containing the DEGs associated with task and tissues. Separation of differentially expressed genes by task was

visualized by performing principal component analysis (PCA) with a 95% confidence ellipse using the ggplot2 v3.4.2 package for R165. For PCA, we used the transformed reads of filtered

transcriptomes from all contigs using the plotPCA function provided by DESeq2. Samples “GO”, “BG” and “YY” showed a divergent expression pattern. To ensure that our results were not

influenced by these deviating samples, we re-run the DEseq2 analyses repeatedly removing sample after sample. This resulted show slight shifts in the number of DEGs in the antennae (2267

with all samples vs. 1960 without “GO”; 1861 without “BG”; and 1862 without “YY”) and in the brain (339 with all samples vs. 227 without “GO”; 272 without “BG”; and 346 without “YY”).

However, the main findings remained similar and a large number of differentially expressed ORs were always found in all analyses (209 with all samples vs. 195 without “GO”; 209 without “BG”;

and 179 without “YY”). Finally, OR genes that were upregulated in each behavioral phenotype were visualized in a volcano plot using ggplot2. All statistical tests and graphical

visualizations were performed in RStudio v.1.4.1106166. IDENTIFICATION OF BEHAVIOR CANDIDATE GENES AND ORS We used gene annotations based on a BlastX search of the _T. longispinosus_

transcriptome compared to a list of different invertebrate proteomes (i.e., _Acromyrmex echinatior_, _Apis mellifera_, _Camponotus floridanus_, _Drosophila melanogaster_, _Harpegnathos

saltator_, _Odontomachus brunneus_, _Temnothorax curvispinosus_) downloaded from the NCBI database with an _E_-value of 1e−5 and below. Clusters containing more than one sequence match per

species were reduced to a single specimen based on the highest blast score. We constructed orthogroups across all of the above species using OrthoFinder167, including amino acid sequences

from the _T. longispinosus_ proteome160, and retained orthogroups containing caste DEGs (Dataset S5) to again compare potential behavioral candidate genes previously identified as involved

in regulating the division of labor in social insects39,42,94,100,155,168,169,170,171. GO enrichment analysis was performed with TopGO v.2.44.0 for R using a Fisher’s exact test for the

different gene sets compared to the whole genome with the weight01 algorithm172. Only annotated GO terms with a _p_ value of ≤0.05 were considered significantly enriched. OR protein sets

were clustered across multiple ant species using OrthoFinder to derive orthologous groups and identify subfamilies for each OR in _T. longispinosus_. To associate orthogroups with previously

identified OR subfamilies, we used OR annotation in _Atta cephalotes_, _Acromyrmex echinatior_ from Engsontia et al.67, and _Camponotus floridanus_, _Harpegnathos saltator_, and _Solenopsis

invicta_ from Zhou et al.63,66. Missing subfamily information was labeled as “unassigned” (Dataset S3). STATISTICS AND REPRODUCIBILITY The experiments were performed in seven replicates.

Each sample contains the pooled RNA from either the antennae or brain of seven ant workers of the respective behavioral phenotype belonging to the same colony, with the colony representing

the level of replicates. Bar graphs show next to median and quartiles, the individual data points. Statistical analyses were performed in RStudio v.1.4.1106, bioinformatics analyses in Bash,

and scripts for both are available on Mendeley. Gene expression analyses were performed using DEseq2, and to exclude the influence of outliers, these were removed individually, and results

presented without them. REPORTING SUMMARY Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. DATA AVAILABILITY Numerical

source data found in Supplementary Data S1 was used to create Fig. 1A and Data S2 for Figs. 2B, C and 3. Raw sequencing reads generated for this study have been deposited in NCBI under

BioProject PRJNA926589. Any remaining information can be obtained from the corresponding author upon request. CODE AVAILABILITY Data analysis and visualization for this study was done using

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references ACKNOWLEDGEMENTS We thank Diego Páez-Moscoso for many helpful discussions and comments throughout the study, Marah Stoldt and Carlotta Martelli for providing helpful comments on

the manuscript, Marion Kever and Jenny Fuchs for technical assistance, and Mark Harrison for providing the manual OR annotations. This project was funded by the Deutsche

Forschungsgemeinschaft (DFG, German Research Foundation) to SF – GRK2526/1 – Projectnr. 407023052. M.A.C. thanks the E.N. Huyck Preserve for support and funding. FUNDING Open Access funding

enabled and organized by Projekt DEAL. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Institute of Organismic and Molecular Evolution, Johannes Gutenberg University Mainz, Mainz, Germany

Marcel A. Caminer, Romain Libbrecht, Megha Majoe & Susanne Foitzik * Institut de Recherche sur la Biologie de l’Insecte, UMR 7261, CNRS, University of Tours, Tours, France Romain

Libbrecht * Institute of Developmental and Neurobiology, Johannes Gutenberg University Mainz, Mainz, Germany David V. Ho & Peter Baumann * Institute of Molecular Biology, Mainz, Germany

Peter Baumann Authors * Marcel A. Caminer View author publications You can also search for this author inPubMed Google Scholar * Romain Libbrecht View author publications You can also search

for this author inPubMed Google Scholar * Megha Majoe View author publications You can also search for this author inPubMed Google Scholar * David V. Ho View author publications You can

also search for this author inPubMed Google Scholar * Peter Baumann View author publications You can also search for this author inPubMed Google Scholar * Susanne Foitzik View author

publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.A.C., R.L., and S.F. conceived the study; M.A.C. conducted the research; M.A.C., M.M., R.L., and

D.V.H. contributed to the development of the data analytical protocol; M.A.C. analyzed the data; and M.A.C., R.L., M.M., P.B., and S.F. wrote the manuscript. CORRESPONDING AUTHOR

Correspondence to Marcel A. Caminer. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Communications Biology_ thanks

Ching-Han Lee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editors: Luke Grinham, Karli Montague-Cardoso, David Favero.

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Task-specific odorant receptor expression in worker antennae indicates that sensory filters regulate division of labor in ants. _Commun Biol_ 6, 1004 (2023).

https://doi.org/10.1038/s42003-023-05273-4 Download citation * Received: 18 April 2023 * Accepted: 22 August 2023 * Published: 02 October 2023 * DOI:

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