Altruistic disease signalling in ant colonies

Domain: physics
Published: 2025-12-02
Editorial outcome: minor_revision

Abstract
Sick individuals often conceal their disease status to group members, thereby preventing social exclusion or aggression. Here we show by behavioural, chemical, immunological and infection load analyses that sick ant pupae instead actively emit a chemical signal that in itself is sufficient to trigger their own destruction by colony members. In our experiments, this altruistic disease-signalling was performed only by worker but not queen pupae. The lack of signalling by queen pupae did not constitute cheating behaviour, but reflected their superior immune capabilities. Worker pupae suffered from extensive pathogen replication whereas queen pupae were able to restrain their infection. Our data suggest the evolution of a finely-tuned signalling system in which it is not the induction of an individual’s immune response, but rather its failure to overcome the infection, that triggers pupal signalling for sacrifice. This demonstrates a balanced interplay between individual and social immunity that efficiently achieves whole-colony health.

Introduction
Sick animals living in groups are often excluded or subjected to aggression by other group members, both to reduce the risk of infection and to gain social or resource-related advantages over the weakened individual1,2. As a result, these individuals often conceal their infection status by, for example, suppressing sickness behaviours in the presence of conspecifics3,4. This is not the case when group members are kin, since relatedness diminishes the conflict of interest between sick and healthy individuals. Therefore, even when group members can detect disease in others, for example, using sickness cues such as altered physical appearance or behaviour, avoidance is often only displayed against non-kin, whilst normal social interactions are maintained with diseased kin5. Diseased individuals can therefore benefit, not only by not concealing, but even from actively communicating their health status to their relatives in order to receive additional care. As such, fungal pathogen-exposed termites display a vibratory signal6, inducing grooming behaviour by nestmates7 and wounded ants produce behavioural and chemical displays attracting their colony members to care for their wounds8,9, which in both cases reduce the signalling individual’s infection risk and hence improves its survival. Helping a relative to survive infection can also indirectly benefit the caregiver by increasing its own inclusive fitness via shared genes with the recipient10. Active disease-state signalling is therefore selected for in groups of relatives, when both the signaller and the signal-receiver gain from the care response. But what happens when the related group member responds not with care, but instead with exclusion or aggression toward the infected individual to protect the group? Should the infected individual still signal its sickness to others, even at the risk of being sacrificed for the benefit of the group?

The evolution of such ‘altruistic signalling’ of infectious disease should be promoted in social groups by two factors: (i) high relatedness, leading to a large indirect fitness gain to the sacrificed individual, if signalling promotes group health, and (ii) low direct fitness loss to the sacrificed signaller, i.e., when its expected future reproductive value is small. Both are fulfilled in the non-reproductive workers of social insect colonies. Workers are typically highly related with one another and produce no offspring of their own, but instead rear the queen’s brood and maintain the colony11. Therefore, the fitness of workers depends on the fate of the colony as a whole. Here, we experimentally test whether altruistic signalling of one’s own sickness indeed evolved in social insect colonies.

Results
Individual pupae were experimentally infected with the pathogen or sham-treated and then kept either with two workers or alone. We employed this full-factorial approach as we speculated that if a signal is costly to produce (e.g., 23) and pupae are able to sense the presence or absence of workers, then they should only signal when both infected and in the presence of the intended receivers, i.e., the workers. As close social interactions in ant colonies often involve the transfer of CHCs through grooming and food sharing – processes that contribute to the colony-wide “gestalt” odour24,25 – pupae, which do not feed at this developmental stage, likely acquire CHCs from workers via external contact. Since the CHC profiles of L. neglectus workers26,27 and pupae22 overlap, we therefore needed to disentangle pupae- and worker-derived chemical compounds. To exclusively quantify the pupa-produced CHCs, we used stable isotope labelling to enrich only the workers’ but not the pupal CHCs with the natural carbon isotope 13C by feeding the workers 13C glucose before the experiment (as detailed in the “Methods”, Supplementary Fig. S1). We focused our analysis on the four previously identified candidate peaks for possible unpacking cues/signals, with two of them (tritriacontadiene, C33:2, and tritriacontene, C33:1) in particular being associated with immune system activation22.

Worker pupae signal their infection in worker presence
Our chemical analysis by use of gas chromatography–mass spectrometry (GC–MS) clearly revealed that only the two immune-associated peaks C33:2 and C33:1 were upregulated, and only by worker pupae that were both infected and kept with workers (Supplementary Fig. S2a; [LM] infection treatment*worker presence interaction: C33:2: p=0.008, C33:1: p=0.036; Supplementary Table S1a), such that their chemical profile deviated from that of the other three groups (Fig. 1a, Supplementary Table S2; all post hoc p-values to the other three groups <0.05). The fact that only the two immune-associated peaks were increased in abundance by infected pupae with workers, and that infection load did not predict abundance of either peak (both p>0.16; Supplementary Table S1b), provides double evidence that this upregulation is not directly brought about by the fungus itself.

Although this CHC change only occurs in infected and hence immune-activated ants, our data reveal that it is not simply a secondary effect of the immune response. The expression patterns of our three tested candidate genes, which represent the three levels of the immune response28 – pathogen recognition (β-1,3-glucan binding protein, BGBP29), immune regulation (peptidoglycan recognition protein SC2, PGRP-SC230,31) and the immune effector activity (Defensin32, Def1; see Methods) – were consistently upregulated in response to infection, while worker presence had no effect (Fig. 1c and Supplementary Fig. S3a [LM] infection treatment: all genes p<0.001; worker presence: all genes p>0.15; Supplementary Table S3a). Therefore, even if all infected pupae equally upregulate their immune gene expression above the healthy baseline, only those in the presence of workers also show an increase in specific CHCs. This indicates that CHC upregulation must be under dynamic host control, allowing the pupae to actively signal their disease status.

Queen pupae do not signal but can restrain infection
While altruistic disease signalling is expected to evolve in sterile workers, the situation is more complex for the daughter queens. By alerting others to destroy them, queen pupae would risk losing potential future reproductive opportunities if they would survive infection. On the other hand, by spreading their infection to their colony, they could incur high indirect fitness costs. We therefore tested if infected L. neglectus queen pupae exhibit altruistic disease signalling similar to that of the worker pupae. We found that – contrary to the worker pupae – none of the four candidate peaks (Fig. 1b and Supplementary Fig. S2b; [LM] all p-values >0.82, Supplementary Tables S4a, S5) nor any of their other CHC peaks (see “Methods”; Supplementary Table S6, [LM] all p-values >0.14) showed differences between the four treatment groups. Thus, we found no evidence of disease signalling in the queen pupae, despite their exposure to a considerably higher pathogen dose than the worker pupae (see “Methods”). Consequently, whilst the signalling infected worker pupae elicited destructive disinfection by the workers, who unpacked them above baseline levels (Cox proportional-hazards regression, treatment effect p=0.0037; Supplementary Table S7), this was not the case for the non-signalling infected queen pupae (p=0.115; Supplementary Table S7). Despite these differences in CHCs between worker and queen pupae, the immune responses of the two castes showed the same pattern. Also in the queen pupae, we found the expression levels of all our candidate genes to be upregulated upon infection, whilst being independent of worker presence (Fig. 1d and Supplementary Fig. S3b [LM] infection treatment: all genes p≤0.001; worker presence: all genes p≥0.15; Supplementary Table S8a). Notably, however, the baseline immune investment under healthy conditions was 35% higher in queen pupae than in worker pupae (Wilcoxon Rank-Sum test; healthy pupae: W=846, p<0.0001), whereas both castes showed similar expression levels when infected (W=1281, p=0.387). This reveals that the documented higher immunocompetence of the queen caste in social insects33,34 already emerges at the brood stage when, as previously shown in other insects, immune activity can already be quite pronounced35,36 despite the fact that pupae do not feed and undergo complete transformation during metamorphosis. Higher baseline immune investment is known to reduce the likelihood of disease development37,38, which may enable queen pupae to better cope with infection compared to worker pupae.

We therefore asked if the absence of signalling in the queen pupae represents a selfish behaviour which puts the colony at risk, or is an honest representation of their higher immunocompetence, allowing them to cope with infection and making the need for signalling obsolete. To this end, we compared pathogen load progression in queen and worker pupae. We found that, whilst infection load steadily increased over the course of infection – with no sign of even plateauing – in the worker pupae (Fig. 1e; all p-values between early, middle and late infection period p<0.0158; Supplementary Table S9a), queen pupal infection load peaked intermediately, but then decreased by almost threefold (Fig. 1f; middle to late infection period p=0.006, Supplementary Table S9b). This suggests that, since the stronger queen immune system was able to reduce infection, whilst the less potent worker immune system was not, both the signalling in the worker pupae and the absence thereof in the queen pupae are honest reflections of the caste-specific differences in individual disease progression during our experiment. Future studies could identify under what infection conditions individual immunity of the queen pupae may fail, and whether this would lead to signalling for own destruction also in the queen caste. We expect this to happen only when pupal immunity is overwhelmed. Our findings show that pupae do not signal the presence of infection nor the activation of their immune system, allowing them the opportunity to clear infections on their own before signalling. This implies the evolution of an early warning system, where fatally infected pupae signal to enable a rapid and targeted colony response.

Signalling relies on complex CHC changes
To confirm a causal—not just correlational—relationship, we performed a bioassay to test whether applying chemical extract from signalling pupae to healthy brood would trigger worker unpacking, using extract from non-signalling pupae as a control (Methods). We indeed found that healthy worker pupae experimentally coated with the extracts of signalling pupae were unpacked more often than those treated with non-signal extract (Fig. 2a; [GLM] one-sided p=0.0496; Supplementary Table S10). Notably, transfer of the signal extract across castes, to healthy queen pupae, equally induced unpacking (Fig. 2b; one-sided p=0.0145; Supplementary Table S10). This allows us to speculate that if queen pupae were to signal any fatal infection that they may develop, workers would respond by unpacking them.

Our bioassay demonstrated that workers rely on the distinct chemical profile of signalling pupae to initiate unpacking. Comparison of the C33:2 (Fig. 2c) and C33:1 (Fig. 2d) GC–MS chromatograms from signal and non-signal extracts indicated that these differences involve not only changes in overall peak intensity (for both C33:2 and C33:1), but also differences in peak shapes (particularly for C33:1) suggesting a possible variation in the isomeric composition of co-eluting positional isomers of the same chain length, bond type and number, but differing in bond position39. Indeed, five isomers of C33:1 were previously found to co-occur in L. neglectus workers, and the presence of several, as yet unspecified, isomers of C33:2 has also been suggested26. Isomeric characterisation using dimethyl disulfide derivatisation (DMDS, Methods), revealed eight positional isomers of C33:2 (Supplementary Table S11 and Supplementary Fig. S4a) and six of C33:1 (Supplementary Table S12 and Supplementary Fig. S4b) in our pupal extracts.

While the overall abundance of the C33:2 isomers (dominated by 11,21-C33:2 and 10,20-C33:2; Supplementary Figs. S4a, S5a) was ~20-times higher in signalling compared to non-signalling pupae, no considerable shift in isomeric composition was detected. For example, 11,21-C33:2, made up 31% of the sum of all eight isomers in non-signalling pupae and 35% in signalling pupae, while 10,20-C33:2 accounted for 21% and 23% respectively (for details see Supplementary Table S11). The C33:1 isomers, on the other hand, while only 3-times more abundant in the signalling pupae, showed considerable proportional changes. In particular, the most prominent isomer, 12-C33:1, exhibited a striking reduction in proportion from 50% in non-signalling pupae to 31% in signalling pupae. In contrast, 13-C33:1 increased from 9% in non-signalling to 16% in signalling pupae, and 11-C33:1 doubled from 9% to 18% (Supplementary Table S12). The remaining C33:1 isomers did not show any substantial differences between signalling and non-signalling pupae. Notably, 10-C33:1 and 9-C33:1 are part of the isomer mixture contributing to the previously identified C33:1 signal peak22, while 7-C33:1 constitutes a separate C33:1 peak that is not upregulated in unpacked pupae22 (Supplementary Table S13, Methods). We therefore found that the chemical profile change in signalling pupae is characterised by a complex interplay: an overall increase in the relative abundance of both C33:2 and C33:1 on the overall pupal bouquet, alongside distinct up- and downregulation of specific C33:1 isomers. It remains unresolved whether ant workers react to the combined effect of multiple components in this composite pattern, or primarily to a single isomer whose abundance changes.

Evidence for both comes from honeybees, where hygienic behaviour – the uncapping of the brood cell and removal of diseased brood17– can be triggered either by the experimental application of single synthetic isomers onto healthy brood alone40, or by a bouquet of multiple compounds41. In addition, shifts in compound ratios have been shown to affect worker responses42. Notably, both C33:2 and C33:1–described here as active signals of fungal disease in ants–have previously been found to be associated with unhealthy honeybees, although it is unclear whether in bees they also function as active signals or merely reflect a passive side effect of infection. Adult bees can show increased C33:2 following viral infection43 and elevated C33:1 after immune-stimulation with bacterial cell wall components44. In honeybee brood, C33:1 is increased across different – viral and mite – infections40,45. While the isomeric composition is still unresolved for most of these infections, the (Z)-10-C33:1 isomer has been identified as a key compound upregulated in virally-infected honeybee brood and is a strong trigger of hygienic behaviour when experimentally applied in its synthesised form40–42. Interestingly, 10-C33:1 is also part of the isomer mixture of the C33:1 signal peak in Lasius ants, and comparison of the retention time of synthetic (Z)-10-C33:1 with our natural extracts revealed that the ants’ 10-C33:1 isomer is present in the same (Z)-stereo-configuration as in the honeybee40 (Supplementary Fig. S6). Since the (Z)-configuration is the only naturally-occurring stereoisomeric form of insect CHCs identified to date46, and is thought to result from their biosynthetic pathways47, it is highly probable that all identified C33:2 and C33:1 isomers found here represent the (Z)-form. This is biologically relevant given that stereoisomers can differ greatly in their biological activity48. Having confirmed the isomeric identity of the 10-C33:1 in bees and ants, we tested whether the synthetic (Z)-10-C33:1 in its pure form, shown to induce hygienic behaviour when applied to honeybee brood40,41, would similarly elicit destructive disinfection in ants. However, it failed to trigger any unpacking in our bioassay (0/41 pupae unpacked; see Methods). This may not be surprising, given that (Z)-10-C33:1 was the least abundant of the isomers in the pupal C33:1 signal peak, comprising only 8% and showing no change in proportion upon signalling (signal to non-signal ratio: 1.00; Supplementary Table S12).

Therefore, despite the overall similarities between bees and ants, the specific isomers acting as indicators of disease are system-specific, suggesting there is no universal disease marker across social insects. It is intriguing, however, that CHCs of similar chain length and with one or two double bonds play an important role in detecting disease states across diverse infections in both ants and bees, suggesting these insects primarily rely on unsaturated CHCs for disease detection. In contrast, sick termites, even when infected with the same fungal pathogen as the ants in our study, show alterations in methyl-branched alkanes49. Unsaturated and methyl-branched CHCs are generally considered to convey more information than saturated CHCs50,51, which may explain their role in disease detection and communication. The differences between termites and social Hymenoptera (bees, wasps, ants) suggest that these two evolutionary distinct lineages of social insects may have evolved different pathways to detect disease, potentially driven by distinct biosynthetic pathways or sensory systems involved in producing or perceiving signs of disease52. Yet, the parallel evolution of informative disease signatures across the social insects highlights the fundamental importance of early disease detection for efficient colony-level disease defence.

Here we describe that ant pupae actively signal their disease to the colony, analogous to how infected cells in a multicellular organism alert immune cells to eliminate them, a self-sacrificial act that preserves the integrity of the whole53. This form of hygienic altruism demonstrates that mechanisms of immune-like defence are not restricted to within individual organisms but can also evolve between individuals in superorganismal colonies, where the fitness of each member depends on the health and success of the reproductive unit they collectively comprise54–56. The signal involves a complex change in the chemical profile produced by pupae when overwhelmed by infection, suggesting a finely tuned balance between individual and social immunity in social insect colonies. Universal destruction of all infected colony members based on passive cues of infection or immune system upregulation would instead disregard varying levels of immunity and recovery capabilities, potentially causing substantial, avoidable losses, including costly-to-rear individuals like new queens. Instead, a mechanism for individual health assessment, wherein individuals signal for destruction only when individual immunity fails, could allow for the simultaneous protection of both individual colony members and overall colony health. That this hinges on precise and complex chemical signalling, rather than broad-spectrum sickness cues, underscores the evolutionary refinement of social immunity systems in distinguishing between recoverable and terminally ill individuals.

Methods
Anthost
As host species, we used the invasive garden ant, Lasius neglectus. We collected several hundred workers, multiple queens and brood of this species from its introduced supercolonial populations26,27 in Jena, Germany (N50°55’54.599” E11°35’8.401”) between 2018 and 2024, and in Seva, Spain (N41°48’32.699” E2°15’42.3”) between 2016 and 2024. Collection of this unprotected species from the field was performed in compliance with international regulations, such as the Convention on Biological Diversity and the Nagoya Protocol on Access and Benefit-Sharing (ABS; permit numbers: ESNC12, ESNC126, SF/0558-0561, EPI 92-2023). After collection, ants were reared in large stock colonies in the laboratory with 30% sugar water and minced cockroaches. Experiments were performed with pupae of a standardised developmental stage (white pupae with black eyes, as visible through the cocoon using a stereomicroscope (Leica S6E) for worker pupae; for queen pupae, the stage can be reliable inferred by checking some pupae in the colony, as they develop highly synchronised in same-age cohorts). Workers were always sampled from the same nest as the respective pupae from the inside of the brood chamber to avoid foragers. All experimental work followed European and Austrian law and institutional ethical guidelines.

Fungal pathogen
As the pathogen, we used the entomopathogenic fungus Metarhizium, whose infectious conidiospores naturally infect ants57 by penetrating their cuticle, killing them and growing out to produce highly-infectious sporulating cadavers58. We infected the pupae with conidiospores (abbreviated as ‘spores’ throughout) of M. brunneum strain Ma275 (KVL 04-57, obtained from J. Eilenberg and N.V. Meyling from the University of Copenhagen, Denmark), which were freshly cultivated from long-term storage on Sabouraud 4% Dextrose Agar plates (SDA; Sigma-Aldrich) at 23°C and had been harvested in sterile Triton X-100 (Sigma-Aldrich, 0.05% in Milli-Q water). Spore germination was confirmed to be >98% one day prior to each experiment.

Pupal CHC profile
Pupal infection. To determine how the pupae’s CHC profile changes with the presence or absence of workers in both castes, we individually exposed each pupa to the fungal pathogen by placing it on a glass slide, applying the fungal suspension and rolling the pupa in the suspension using soft forceps. Control pupae were treated the same, except for using Triton X-100 solution as a sham treatment. Pupae were then left to air-dry on the slide before putting them in a plastered dish (90x35mm, Licefa GmbH) for three days before the start of the experiment. We used 1µL of a 1x106 spores/mL fungal suspension for the exposure of worker pupae and 2µL of a 1x107 spores/mL fungal suspension for queen pupae, and the same respective volumes of sham solution for the control pupae. Using the below-detailed fungal load determination by quantitative real-time PCR (qPCR), we determined that this exposure procedure resulted in an approximately 10-fold higher exposure dose for the queen pupae than the worker pupae (queen pupae: mean 1.587x10−3 ng/µL, maximum 2.232x10−3 ng/µL, n=3; worker pupae: mean 1.603x10−4 ng/µL, maximum 2.158 x 10−4 ng/µL, n=7). Our application dose of 1µL of a 1x106 spores/mL fungal suspension resulted in a realised exposure dose per worker pupa of approximately 95 spores22, allowing us to infer an approximate load of 940 spores per queen pupa, both presumably being within natural exposure range, given single cadavers produce up to 12 million spores59 and soil can contain 5000 spores / gram60. We exposed queen pupae to this higher spore load, since they are much larger than worker pupae (mean queen pupa length: 5.7mm, width: 2.5mm; n=4; mean worker pupa length: 2.9mm, width: 1.1mm; n=4, resulting in approximately 4-fold greater surface area and 9-fold higher volume of queen pupae compared to worker pupae). Preliminary data also showed that approximately half this dose was insufficient to induce a successful infection in queen pupae. This is in line with reports that, generally, social insect queens have higher immunocompetence than workers34 and, in particular, that Lasius queens show higher immune gene expression than workers33.

To allow for the successful establishment of infection, pupae were kept in plastered dishes (90x35mm), after exposure, for three days in the absence of workers (as in ref. 22), as otherwise the sanitary care provided by accompanying workers would interfere with the infection process due to spore removal and disinfection61,62. Equally, control pupae were kept without workers for the same duration after their exposure to the sham treatment to ensure they were the same age as the fungus-treated pupae. This incubation period and all following experimental procedures took place in a temperature and humidity-controlled room at 23°C, 65% relative humidity (RH) and a 12h day/night light cycle and the plastered dishes were watered every 2-3 days to keep humidity high.

Experimental setup. After the three days of fungal (or sham) infection establishment, individual pupae were placed into a plastered dish (35x10mm; Falcon or SPL Life Sciences), either alone or with two workers that originated from the same colony as the pupa, and which had been fed with 13C glucose as detailed below. Using a full-factorial design, we thereby set up four treatment groups: infected pupae without workers (I+W-), infected pupae with workers (I+W+), control pupae without workers (I-W-) and control pupae with workers (I-W+). From each treatment, we sampled pupae over a 42-hour period after setting them up with the workers, at seven time points in intervals of six hours (i.e., at 6, 12, 18, 24, 30, 36 and 42 h). At each time point, we collected both infected and control pupae and recorded if a pupa had been unpacked in the presence of workers. This regular sampling was performed to ensure we only analysed pupae that were still able to modulate their cuticular hydrocarbons (CHCs), and had not yet been damaged by the destructive disinfection by the workers. To this end, we excluded worker pupae that appeared themselves damaged or dead, as identified by a ‘shrivelled’ morphology or a change in colouration (n=27). We also excluded replicates, where one or both accompanying workers died during the experiment (n=18), and three pupae were misplaced during the experiment. From these remaining 358 replicates, 35 had to be excluded after chemical analysis as they did not match our quality criteria as detailed below, leading to a final sample size of 323 worker pupae, of which 69 I+W-, 133 I+W+, 64 I-W-, 57 I-W+, from both the Jena (n=168) and the Seva (n=155) populations. For the queen pupae, the same quality criteria were applied during the experiment. Only one queen pupa did not match the chemical criteria, leading to 103 analysed queen pupae, of which 19 I+W-, 45 I+W+, 19 I-W-, 20 I-W+, all from the Jena population). For each pupa, we also obtained the pooled CHC profiles of its two accompanying workers (190 pools of the 380 accompanying the worker pupae and 65 pools of the 130 workers accompanying the queen pupae) to obtain their 13C integration levels. We froze each pupa with its cocoon (as in Pull et al. 201822) in a brown glass vial (1.5mL, Agilent) closed with one-component-closure-caps (Agilent) at −70°C, to store them for later chemical extraction for determination of the pupal surface chemicals, followed by DNA extraction and quantification of the fungal load. For replicates containing workers, both workers were pooled in a single glass vial for later chemical analysis (detailed below). We conducted the experiment separately for worker and queen pupae, with each experiment lasting five days, from the time of exposure, over the three days of isolation to the last sampling point, each carried out in a single block.

13C-enrichment of accompanying worker-CHCs. In this study, we wanted to compare the pupal CHC production depending on both their infection status (infected I+ vs uninfected I-) and the presence or absence of attending workers (W+ vs W-). As it is known that colony members exchange CHCs to form a colony “gestalt” odour24,25, we developed a method to exclusively quantify the pupa-produced subset of the CHCs found on the pupae, removing any possible worker-applied compounds, in order to accurately determine pupal signalling. To do this, we used stable isotope labelling63,64 of the worker compounds by feeding workers glucose enriched with 13C, which is a stable natural isotope of 12C, and accounts for 1.1% of environmental carbon. By feeding workers the 13C-enriched glucose (99% 13C compared to the natural abundance of ~1.1%), 13C becomes incorporated into the workers’ CHC compounds at elevated levels. When these 13C-enriched workers tend normal pupae (i.e., pupae from stock colonies that had not been reared on labelled 13C-glucose), they transfer their 13C to the pupae, altering the natural 12C to 13C ratio in the pupal extracts (see below). Quantification of the 12C to 13C ratio of each peak of (i) the tending workers (to determine the exact 13C integration level into the workers’ CHCs for each peak and replicate) and (ii) the pupa kept with these workers, will therefore indicate which proportion of the CHC is from non-enriched pupal origin and which from enriched worker origin. By using the formula detailed below to exclude the worker-applied proportion, we were able to calculate the quantity of each CHC peak produced exclusively by each pupa, as a function of its infection status and the social context (presence or absence of workers).

Worker ants were put into experimental containers (90x35mm) in groups of 50 (worker pupae experiment: n=20 groups; queen pupae experiment: n=11 groups) and fed exclusively with 13C-enriched glucose solution (D-Glucose-13C6, 99 atom %, Eurisotop; 10% weight/volume in water) for three weeks prior to being placed with the pupae in the experiment. Throughout these three weeks, the pupae, later used in the experiment, remained in the stock colonies, and hence had not been able to incorporate labelled glucose as larvae. After these three weeks, two workers from the same feeding dish were put with an individual pupa originating from the same stock colony, as detailed above.

Chemical analysis of pupae-derived CHCs
Gas chromatography–mass spectrometry. We used gas chromatography–mass spectrometry (GC–MS) to determine the composition of CHCs of worker and queen pupae, as well as their attending workers (where appropriate, i.e., in I+W+ and I-W+). To this end, we extracted pupal CHCs from individual worker and queen pupae, as well as the worker CHCs from the pool of both workers per replicate, by adding 90µL n-pentane solvent (Supelco) to the vials in which they had been collected. Vials were closed with aluminium-faced silicon septa caps (Agilent). Extractions were performed with the solvent for 5 min under gentle agitation at room temperature. The supernatant was transferred to glass vials with 350µL glass inserts and sealed with aluminium-faced silicon septa (Agilent). The n-pentane solvent contained two internal standards at the beginning and the end of the known range of cuticular hydrocarbons of L. neglectus (C27-C37)22,26,27, n-tetracosane and n-hexatriacontane at 0.1µg/mL concentration (both C/D/N Isotopes), both fully deuterated to enable spectral traceability and separation of internal standards from ant-derived substances. The extracts from the different treatment groups were run in a randomised manner, intermingled with blank runs (containing only n-pentane), and handling controls, using GC–MS (gas chromatograph GC7890 coupled to mass spectrometer MS5975C; Agilent).

A liner with one restriction ring filled with borosilicate wool (Joint Analytical Systems) was installed in the programmed temperature vaporisation (PTV) injection port of the GC, which was pre-cooled to −20°C and set to solvent vent mode, and 50µL of the sample extracts were injected automatically into the PTV port at 40mL/s using an autosampler (CTC Analytics, PAL COMBI-xt, CHRONOS 4.2 software; Axel Semrau) equipped with a 100µL syringe. Directly after injection, the temperature of the PTV port was increased to 300°C at 450°C/min, thereby vaporising the sample analytes and transferring them to the column (DB-5ms UI; 30m × 0.25mm, 0.25μm film thickness; Agilent) at a flow rate of 1mL/min. Helium was used as the carrier gas at a constant flow rate of 3.0mL/min for 2 min, then decreased to a constant flow rate of 1.1mL/min at 100mL/min2. The oven was programmed to hold 35°C for 4.5min, then ramp to 325°C at 20°C/min, and hold this temperature for 10min. The GC–MS transfer line was set to 325°C, and the mass spectrometer (MS) was operated in alternating TIC-SIM mode with a scan range of 35–600 amu in total ion current (TIC) mode, using electron ionisation mode (70 eV; ion source 230°C; quadrupole 150°C, with a detection threshold of 150). Disentanglement of worker-applied and pupa-produced compounds (using the below detailed quantification of 12C and 13C) was based on the SIM (selected ion monitoring) mode, where the ions 57.1, 58.1, 59.1, 60.1, and 61.1 were selected. In addition, a C7-C40 saturated alkane mixture (in steps of 1 at a concentration of 0.1µg/mL for each alkane in n-pentane) was run as an external standard, to enable calculation of Kováts Retention Indices (RIs)65,66 and to correct for possible shifts in retention time (RT).

Compound peaks were extracted from the total ion current chromatograms (TICCs) of representative sample runs, using a deconvolution algorithm (MassHunter Workstation, Qualitative Analysis B.07.00; Agilent). CHC identification was performed by comparing the mass spectrum and RI of each compound by manual interpretation of diagnostic ions, as well as by comparison to previous cuticular hydrocarbon (CHC) compounds identified for L. neglectus adult workers26,27 and worker pupae22, as detailed in Supplementary Table S13 and with representative mass spectra deposited under doi.org/10.15479/AT-ISTA-20471. For reasons outlined below, this study includes only a subset of previously described CHCs, specifically those that met our criteria for accurately determining 13C levels using the method we developed to disentangle worker-applied from pupa-produced CHCs.

Besides the pupal CHCs, we also analysed the CHC peaks of their accompanying workers by the above-mentioned GC–MS procedures, using automatised integration of the peak area of each peak and standardisation of the amount of each peak to its closest internal standard eluting before (MassHunter Workstation), thereby correcting for possible injection differences. For each peak, we quantified the 12C and 13C proportion based on the SIM scans, using the generally highly abundant ion 57.1 as quantifier ion for 12C (as it represents the fragment 12C4H9), and the sum of ions 58.1, 59.1, 60.1 and 61.1 as quantifier ions for 13C, as they reflect the level of 13C enrichment (13C1 12C3H9, 13C2 12C2H9, 13C3 12C1H9 and 13C4H9 respectively; simplified scheme due to low natural abundance of other possible isotopes). Since 13C makes up 1.1% of environmental carbon, its natural level in C4H9 – and hence the baseline found in non-enriched samples (Supplementary Fig. S1) – is 4.4%.

Using this method, we found that the CHC profiles of the workers fed with 13C-labelled glucose do indeed show peak-specific 13C levels increased above the natural values of ~4.4%. Moreover, these workers transferred CHCs to the pupae during social contact: pupae kept with workers showed increased 13C levels (>4.4%), whereas pupae kept without workers did not, which was equally true for worker (Supplementary Fig. S1a) and queen (Supplementary Fig. S1b) pupae. Notably, the intensity of 13C-enrichment differed between worker groups (likely depending on differences in feeding activity), yet the difference between individual workers within feeding groups was negligible (as workers of the same feeding group differed only by a mean of 2.2% in their proportion of 13C in peak C33:2 and 3.1% in C33:1, as determined by quantification of n=19 additional pairs of workers from 4 feeding groups). To determine the level of 13C incorporation into the two workers per replicate, we pooled both individuals for a joint extraction. This allowed us to obtain the replicate-specific worker 12C and 13C proportion for each of their CHC peaks, which was necessary to estimate the amount of each peak produced by each pupa.

Subtraction of worker-transferred CHCs from total pupal profiles. 13C labelling of worker-derived CHCs allowed us to subtract the transferred worker CHCs from the total peak amount measured in the pupae (pupa- and worker-derived). This enabled us to quantify the CHCs produced exclusively by the pupae, which we then compared between treatments. As only the workers but not the pupae had been 13C-enriched at the start of the experiment, the proportion of 13C in solely pupa-produced CHCs reflected the natural 4.4% in the four C atoms (as also confirmed by pupal CHCs in the absence of workers, Supplementary Fig. S1). Consequently, any 13C-content exceeding the natural background level of ~4.4% in a peak indicates application of the 13C-enriched CHCs from the labelled workers. Since we measured, for each peak and replicate, the level of 13C incorporation into the workers’ CHCs resulting from their feeding of the 13C-labelled glucose, we could determine both the 13C proportion in workers (as quantified from the experiment) and in pupae (natural baseline of 4.4%). Given the measured value for total (pupa- and worker-derived) 12C and 13C per peak, we could therefore disentangle the pupa- and worker-derived contribution and reach the purely pupa-produced quantity (Apupa) for each peak by the following formula:

Apupa = (A12 * φW13 - A13 * φW12) / (φP12 * φW13 - φP13 * φW12) (1)

where, for each peak:
φW13 or φW12 = the proportion of 13C or 12C of the peak measured in the accompanying workers (quantified from the replicate-specific worker extract)
φP13 or φP12 = the natural proportion of 13C or 12C in the unenriched pupal CHC (set to 0.044 and 0.956, respectively)
A12 = the total amount of 12C of the peak quantified from the pupal extract (reflecting both pupa- and worker-derived 12C)
A13 = the total amount of 13C of the peak quantified from the pupal extract (reflecting both pupa- and worker-derived 13C)

Note that this calculation was performed for each peak and replicate, using the amounts obtained by standardisation to the closest internal standard eluting before the peak (as detailed above). From the previously described CHCs of L. neglectus worker pupae22, six compounds (3-methylhentriacontane; 13,23-dimethylpentatriacontane; 11,25-dimethylpentatriacontane; 7,11,23-trimethylpentatriacontane; n-hexatriacontane and one unidentified) could not be included in the current analysis, as they were either co-eluting with other compounds impacting quantification or 13C was undetectable in many of the pupal and worker samples (note that four of these excluded compounds were analysable in the queen pupae due to higher compound abundance, yet their inclusion did not alter our findings so for consistency reasons we report only the CHCs that are conclusive for both worker and queen pupae). Worker and queen pupae shared the same peaks (Supplementary Table S13).

Furthermore, we could not include 35 worker and one queen pupae samples, which had been originally sampled, but for which an accurate assessment of their pupa-produced CHC quantity was not possible for all peaks (these pupae are already deducted from the final sample sizes reported above). This was either because – likely due to natural variation or measurement inaccuracies at low peak abundances – the 13C proportion of some of their peaks had a higher value than that of accompanying workers (worker pupae: n=21; queen pupae: n=0), or as their 13C was below detection threshold in some peaks, which were typically overall of low quantity (worker pupae: n=14; queen pupae: n=1). When the measured 13C proportion of a peak was below 4.4% (similarly likely due to natural variation around the 4.4% average or measurement inaccuracies), which occurred in 10.68% of the worker pupae peaks (621 out of 5814) and 18.39% of the queen pupae peaks (341 out of 1854), we used the measured value as pupa-produced amount because workers cannot have transferred said peak. Similarly, when a peak was undetectable in both 12C and 13C forms, or only detectable in 13C, in the accompanying workers (134 cases in the worker pupae and 85 cases in the queen pupae), or when no workers were present in the treatment group (i.e., in all I+W- and I-W- groups), the total measured value in the pupa was taken as the pupa-produced amount. For each pupa-produced peak, we then calculated its relative proportion in the overall pupal chemical bouquet and report these relative abundances (standardised amount of the respective peak / sum of the standardised amounts of all 18 peaks). Our main focus was to see whether the relative abundances of the four CHCs that were identified by Pull et al. 201822 as possible candidate compounds for either a cue or signal were differentially modulated by the pupae in response to treatment.

Immune gene expression
We repeated the experiment for both worker and queen pupae, to analyse how the expression of three candidate immune genes depended on pupal caste, infection status and worker presence. Since we were not aiming at measuring pupal CHCs in this experiment, no 13C-labelling of the accompanying workers was required. We used one gene representing each of the three stages of the immune reaction: β-1,3-glucan binding protein (BGBP) for pathogen recognition29, peptidoglycan recognition protein SC2 (PGRP-SC2) for immune regulation30,31 and the antimicrobial peptide Defensin 1 (Def1) for immune effector activity32,67. Several pupae were excluded from the analysis due to death or mould during the experiment (n=12 queen pupae), incorrect developmental stage (n=3 queen pupae), or poor RNA quality (n=9 worker pupae). This resulted in a final sample size of 117 worker pupae (19 I+W-, 58 I+W+, 20 I-W-, 20 I-W+) and 62 queen pupae (17 I+W-, 20 I+W+, 11 I-W-, 14 I-W+). All pupae and their corresponding workers originated from the Jena population.

RNA extraction. Before extracting their RNA, pupae were homogenised using a TissueLyser II (Qiagen) with a mixture of one 2.8mm ceramic (VWR), and five 1mm zirconia (BioSpec Products) and approx. 100mg glass beads (425–600µm, Sigma-Aldrich). Homogenisation was carried out in two steps (2x2min at 30Hz). Pupal RNA was extracted using either the Maxwell RSC simplyRNA tissue kit (Promega) or the AllPrep DNA/RNA Mini kit (Qiagen). Both kits were used following the manufacturerʼs instructions, using a final elution volume of 50µL (Promega kit) or 14µL (Qiagen kit) RNase-free water. To ensure removal of residual DNA contaminations we performed a DNase I treatment (Sigma-Aldrich). cDNA was synthesised using iScript cDNA synthesis kit (Bio-Rad) according to the manufacturerʼs recommendations, using 11µL of DNase I treated RNA as starting material.

Gene expression. Expression levels of the three immune genes BGBP, PGRP-SC2 and Def1, as well as the housekeeping gene 28S Ribosomal Protein S18a (RP-S18a68), were analysed in 20μL reaction volumes using KAPA SYBR Fast qPCR master mix (Roche) and 4 pmol each of specific primers (Sigma-Aldrich; for primer sequences see Supplementary Table S14) on a Bio-Rad CFX96 real-time PCR detection system. Two microliters of the either undiluted or 1:10 diluted cDNA (4µL for some samples, as expression values for defensin were low) were added per reaction, and each sample was analysed in duplicate or triplicate wells. Each run contained an absolute negative control. Primer efficiency was determined to lie between 90 and 105% for all primer sets using standard curves of 10-fold dilutions. The following amplification programme was used: 95°C for 5 min, followed by 40 cycles of 10 s at 95°C and 30 s at 55°C (Def1: 20 s at 60°C). Following each run a melting curve analysis was run to monitor primer specificity. Immune gene expression levels were determined using the standard curve method and were normalised to the expression level of the housekeeping gene RP-S18a.

Pathogen load quantification
We further quantified the ‘fungal load’ of all fungus-treated worker and queen pupae from the CHC experiment after having extracted their surface chemicals (as detailed above). One worker pupa was lost during DNA extraction, leading to a final sample size of n=201 worker and n=64 queen pupae. We also analysed all sham-treated pupae (except for three samples that could not be analysed due to technical issues; leading to 119 control worker pupae and 38 control queen pupae), and used their highest value to set the concentration threshold above which we could confidently identify fungal infection and perform an accurate fungal load quantification using real-time PCR (qPCR), quantifying absolute fungal DNA load using the standard curve method (detailed below). With a value of 7.2x10-4 ng/µL this threshold value was approximately 500-fold and 3000-fold lower than the mean fungal load of the worker pupae (3.9x10−1 ng/µL) and queen pupae (2.3 ng/µL), respectively. We also quantified the fungal load of seven worker and three queen pupae samples frozen straight after exposure, to obtain the worker pupae and queen pupae-specific ‘exposure dose’ (reported above). As these exposure doses differed between the castes, we calculated the ‘infection load’ for each pupa as its measured fungal load relative to the maximum caste-specific exposure dose to determine the infection progression after exposure.

DNA extraction and qPCR. We extracted and quantified Metarhizium DNA per infected ant pupae by targeting the sequence of the fungal ITS2 gene as in Giehr et al. 201769. Prior to DNA extraction, the samples were homogenised as detailed above. DNA extractions were performed using the DNeasy 96 Blood & Tissue Kit (Qiagen), following the manufacturerʼs instructions, with a final elution volume of 50μl Buffer-AE. qPCR was performed using primers targeting the Metarhizium brunneum ITS2 rRNA gene region as in Giehr et al. 201769 (primer sequences: Supplementary Table S14). Reactions were performed in 20μL volumes including 1x KAPA SYBR® FAST qPCR Master Mix (Roche), 3 pmol of each primer (Sigma-Aldrich) and 2μL of extracted DNA. The amplification programme was initiated with a first step at 95°C for 5 min, followed by 40 cycles of 10 s at 95°C and 30 s at 64°C. Quantification was done based on the standard curve method, using standards covering a range from 10−1 to 10−5 ng/µL fungal DNA (measured using a NanoDrop spectrophotometer, Thermo Fisher Scientific). Each run included the standards and a negative control. Samples, as well as standards and controls, were run in triplicates. Specificity was confirmed by performing a melting curve analysis after each run.

Generation of signal and non-signal extracts
To test for a causal relationship between the CHC profile of the pupae and worker unpacking, we obtained the chemical extract of worker pupae that had been infected and unpacked by the workers (‘signal extract’) and of sham-treated pupae that did not elicit worker unpacking (‘non-signal extract’). We transferred the extracts onto worker and queen pupae in a bioassay, testing if the CHCs by themselves elicited unpacking behaviour towards the otherwise healthy brood. We also characterised the isomeric compositions of the identified signal peaks C33:2 and C33:1, and determined how they differed in the signal and non-signal extract (as detailed below).

Generation of signalling and non-signalling pupae. The bioassay, in which we experimentally transferred the extracts onto worker and queen pupae (as detailed below), required a high number of signalling worker pupae. To generate these, age-controlled worker pupae (as described above) were exposed to 1µL of a spore suspension at a concentration of 1x109 spores/mL. This corresponds to the ‘high dose’ defined by Pull et al. 201822, in contrast to the ‘medium dose’ (1x106)22 used in the experiments above. This was appropriate since Pull et al. had established that the high dose results in a higher unpacking rate, while worker behaviour remains otherwise unchanged22. In addition, our detailed chemical comparison during method establishment found no distinguishable difference in CHC peak patterns between doses, indicating equivalent CHC compositions. Due to this higher exposure dose and hence faster disease development, we also shortened the isolation period of the pupae to two days before adding two nestmate workers. Sham-treated pupae were produced as in previous experiments, and workers were added to create the I-W+ treatment as the closest control of non-signalling pupae to the signalling group (I+W+). All fungal and sham-exposed pupae were individually placed in plastered dishes (35x10mm, SPL Life Sciences) directly after the applied treatment had dried. After worker addition, we checked pupae for unpacking regularly every 6-10 h over a period of 42 h, to make sure signalling pupae were collected shortly after unpacking and before being destroyed by the workers. We collected ‘confirmed signalling pupae’ that had been unpacked after fungal treatment and ‘confirmed non-signalling pupae’ that remained cocooned after sham-treatment. Pupae were collected in clear glass headspace vials (10mL, Thermo Fisher Scientific) and frozen at −70°C for further use in the bioassay and chemical analysis.

Bioassay determining unpacking of healthy pupae after extract transfer
Generation of CHC extract for transfer onto pupae. For application onto healthy worker and queen pupae, we extracted a total of 681 worker pupae (343 signalling and 338 non-signalling) in 22 pools of on average 31 pupae (min. 25, max. 37), always containing only pupae from the same treatment and population (120 pupae from Seva and 561 from Jena). The pools were extracted as detailed below, and used to transfer signal extract to healthy pupae that had been randomly sampled from their colonies the day before the bioassay, age-controlled as above, and kept overnight with workers from the same colony in plastic containers (90x35mm) with humidified, plastered ground. In total, the signal extract was transferred to 113 pupae and the non-signal extract to 102 pupae, so that each treated pupa received an extract equivalent of approximately three source pupae (as detailed below).

Extracts were generated by adding 300µL n-pentane per pupa to the 10mL clear glass vials containing the pooled pupae (average n=31 / vial, as detailed above), and incubated at room temperature for 10min, after which the supernatant containing the extracted CHCs was transferred to a brown glass headspace vial (10mL, Thermo Fisher Scientific). We then rinsed the original extraction vial to dissolve all remaining CHCs with another 1mL of n-pentane and added it to the vial containing the supernatant, before evaporating the extract in a dry bath (Labnet International) at 45°C, partially aided by blow-drying with nitrogen gas (taking approx. 1h). We dissolved this dried extract by adding 800µL n-pentane and vortexing at maximum speed for approx. 15sec and transferred it to a 1.5mL brown glass vial. To dissolve all CHCs, we washed the original vial a second time with 800µL n-pentane, adding the 800µL into the vial. After solvent evaporation, the residue was taken up in two washes of 80µL n-pentane and transferred to a new 1.5mL glass vial, now containing a 150µL glass micro insert (Chroma Globe). After solvent evaporation, the walls of the micro-inserts were rinsed with 30µL n-pentane and dried one last time, thereby concentrating the CHCs at the bottom of the insert. The dry extracts were stored at −20°C under nitrogen gas until use in the bioassay the day after.

Extract transfer onto healthy pupae. We transferred the signal extract to 78 worker pupae (with a final sample of 76 since two got damaged during the procedure) and 35 queen pupae, and non-signal extract to 64 worker and 38 queen pupae, to test if the CHC profiles per se contained the unpacking trigger and if unpacking could also be elicited in the queen pupae.

For application onto the healthy pupae, we dissolved the extracts by adding 1µL n-pentane per extracted pupa, leading to an average volume of 31µL (min. 25µL, max 37µL) per micro insert, depending on initial pool size. Previous method establishment had revealed that this volume in the micro insert minimises evaporation of the volatile n-pentane. Therefore, 8–13 healthy pupae could be treated per batch by four consecutive applications of a 0.5µL droplet of either signal or non-signal extract, leading to a total application volume of 2µL per pupa, with the same volume applied to queen and worker pupae. We confirmed that the order of application of the extract had no effect on a pupa’s unpacking probability, revealing that the variation inherent to the application procedure did not lead to a biological effect. We applied the final volume of 2µL in four steps of 0.5µL each to ensure that the applied extract dried on the pupal surface and did not run off to the underlying glass plate (cleaned with n-pentane between batches), on which all receiving pupae of each batch were placed before the transfer. To achieve this high yield, we cooled the extract vials before use at 4°C and kept them in a cool metal block on ice during the experiment, as well as used a pre-cooled low-volume volume-syringe (Trajan Scientific), stored at −20°C before each round of application. After application, all treated pupae per batch were transferred individually to a dish (Ø=35mm) with plastered ground, and two workers from the same colony were added to each pupa. We ran the experiment separately for the worker and the queen pupae, each in multiple blocks (three blocks for the worker pupae and four for the queen pupae). After blinding the treatment information and intermingling the batches, we checked each pupa for unpacking by the two workers within 12 h after application for the worker pupae and 4 h for the queen pupae, as method establishment revealed that the ants reacted about 3 times faster to the manipulation of queen than worker pupae. In fact, after 4 h, only 3.9% of signal-treated and 1.5% of the non-signal-treated worker pupae had become unpacked, whereas in the same time, 14.3 % of the signal-treated and 2.6% of the non-signal-treated queen pupae were unpacked.

Comparative treatments. In addition to the transfer of worker pupae-produced extracts, we performed the following applications, all on worker pupae from Jena (total n=62). Application of pure n-pentane as a negative control did not induce unpacking in any of the pupae (n=21), confirming that the procedure by itself does not induce unpacking. We also applied the compound (Z)-tritriacont-10-ene ((Z)-10-C33:1; LGC Group), which elicits removal of treated honeybee pupae from their brood cell40, but which we did not find increased in our signal extract (see below and Supplementary Table S12). We applied (Z)-10-C33:1, dissolved in n-pentane at either a concentration of 2.5ng/µL (n=21) or 4ng/µL (n=20), and thus in a final dose of 5 resp. 8ng per pupa, to remain within the natural abundance of C33:1 (RI 3281) in our samples of approx. 9ng/pupa.

Isomer characterisation of the CHC signal
We used one pool each of 20 signalling resp. non-signalling pupae (from Jena) to analyse the isomeric composition of the signal CHCs.

Generation of extract for isomer characterisation. We obtained signal and non-signal extract for a pool of 20 worker pupae each, by adding 300µL n-pentane per pupa to the 10mL clear glass vials, and incubation at room temperature for 10min, after which the supernatant containing the extracted CHCs was transferred to a brown glass headspace vial (10mL). After solvent evaporation, the samples were redissolved in 100µL n-pentane. To remove polar compounds, we then passed these extracts through a conditioned SPE (solid-phase extraction)-column filled with unmodified silica gel (CHROMABOND® SiOH, 1mL, 100mg, Macherey-Nagel). The hydrocarbons were then eluted with 4mL of n-pentane, the solvent evaporated, and the samples redissolved in 600µL n-pentane (30µL per pupal equivalent), to be used for the generation of native chromatograms and further DMDS derivatisation.

GC–MS of native (non-derivatised) signal and non-signal extract. From each sample, 60µL were transferred to an autosampler vial (with fixed insert 350–10µL, clear glass, Agilent). The solvent was evaporated and the samples redissolved in 110µL n-pentane containing our deuterated internal standards. The samples were run on the GC–MS, with the following changes to the above method: the PTV injection port was set to 34°C and the alternating TIC-SIM mode was used, with selected ions being 66.2, 460.9 and 462.9, with a dwell time of 20ms each. In the same sequence and with the same settings, we ran the C7-C40 saturated alkane mixture as above, yet also (Z)-tritriacont-10-ene ((Z)-10-C33:1, 1µg/mL in n-pentane), which had been identified as a compound eliciting hygienic behaviour in honeybees40. Overlay of the SIM chromatograms of these native signal and non-signal extracts for C33:2 (m/z 460.9; Fig. 2c) and C33:1 (m/z 462.9, Fig. 2d) was used to compare peak shapes, indicative for differences in both quantitative abundances and isomeric compositions between the two extracts. Overlay of the signal extract with the (Z)-10-C33:1 standard (Supplementary Fig. S6) was used to indicate the retention time of the C33:1 isomer with double bond at position 10, (i) allowing interpretation of the relative positioning of the other C33:1 isomers (ranging from double bonds at positions 13 to 7) in our samples, and (ii) revealing that also the C33:1 isomers in our samples similarly are present in (Z)-configuration. The relative retention times of C33:2 vs C33:1 in our samples and the fact that the (Z)-form is also the only so far reported isomer configuration found for alkenes and alkadienes across the social insects46, further makes the (Z-Z)-configuration highly likely also for our C33:2 isomers.

GC–MS of DMDS-derivatised signal and non-signal extract. To identify the isomers of C33:2 and C33:1 in our samples, we subjected 420µL of the extracts, concentrated to 50µL, to DMDS derivatisation. To obtain the positions of the double bonds of the isomers, we followed the protocol by Carlson et al. 198970. The 50µL of concentrated samples in n-pentane were mixed with 50µL DMDS (Sigma-Aldrich) and 25µL of a 6% iodine solution (w/v iodine in diethyl ether, both Sigma-Aldrich). The reaction mixtures were held in 1.5mL vials closed with PTFE/silicone screw caps (Agilent) at 40°C for 5h, before they were diluted with 1mL n-pentane and transferred to a 10mL clear glass headspace vial (Thermo Fisher Scientific), where they were further diluted with n-pentane to a total volume of 4mL. The same volume of 5% sodium thiosulfate pentahydrate (w/v in water, both Sigma-Aldrich) was added, the mixture vortexed, the organic phases removed and dried over anhydrous sodium sulfate (Sigma-Aldrich). The extracts were decanted, the solvent evaporated, and the samples redissolved in 110µL n-pentane for GC–MS measurement. For this, the GC–MS method was adapted as follows: the PTV injection port was set to 34°C and the final temperature was set to 330°C. The oven programme was ramped to 350°C (20°C/min) and held on this temperature for 15min. The GC–MS transfer line was set to 355°C and the scan range of the MS was extended to 700 amu. The selected ions for SIM mode were 61.0, 145.1, 173.1, 187.1, 201.1, 215.2, 229.2, 507.6, 509.6, 556.7 and 648.7, with a dwell time of 12ms each. The C7-C40 saturated alkane mixture was used to estimate the Kováts RIs for the DMDS-adducts of the X-C33-monoenes. Since the X,Y-C33-dienes eluted after the C40 reference alkane, an additional alkane (C44, contained in a C12-C60 mixture (ASTM 5442 C12-C60 standard, Supelco) was measured to extend the reference range for RI estimations. For the di-adducts eluting beyond C44, retention times of hypothetical n-alkanes were extrapolated using a polynomial regression model fitted to the retention times of the known n-alkanes. The extrapolated retention times for C47 and C48 were then used in the Kováts equation to calculate the RIs of the C33:2-DMDS-di-adducts. While no previous isomeric information was available for C33:2 of L. neglectus, we found all C33:1 isomers previously described for L. neglectus workers26, plus tritriacont-9-ene, 9-C33:1) in our pupal samples. We show the structures of the annotated C33:2 isomers and C33:1 isomers in the inferred most likely (Z-Z)- and (Z)-configuration (Supplementary Fig. S4a for C33:2 and S4b for C33:1, respectively) and the mass spectra for the two dominant C33:2-DMDS-di-adducts (Supplementary Fig. S5a) and for all annotated C33:1-DMDS-mono-adducts (Supplementary Fig. S5b).

Annotation of X-Y-C33:2 and X-C33:1 isomers. We followed the method by Carlson et al. 198970 for isomer annotation. SIM was chosen to extract the molecular ion (M)+= m/z 648.7, as well as the diagnostic fragment ion (M-141)+= m/z 507.6 common to all DMDS-di-adducts of X,Y-C33:2. The corresponding (A)+ and (D)+ fragment ions were determined by inspection of their SIM chromatograms and extracted ion chromatograms (EICs). When the supposed fragment ion pair showed comparable retention behaviour (retention time, peak shapes, parallel increase and decrease of their abundances over the peak width) and also plausible abundance ratios of the (A)+ and (D)+ ions, they were considered as a matching ion pair, indicating the double bond positions in the respective C33:2 isomer. SIM was further chosen to extract the molecular ion (M)+= m/z 556.6, as well as the diagnostic fragment ion (M-47)+= m/z 509.6 common to all DMDS-mono-adducts of X-C33:1. The (A)+ and (B)+ fragments for the mono-adduct of each positional isomer were determined by inspection of the averaged mass spectrum and the respective extracted ion chromatograms (EICs). When the supposed (A)+ and (B)+ fragments ions showed the same retention behaviour (as above for C33:2) and fitted mathematically ((A)++(B)+=(M)+), we considered them a matching ion pair, indicating the double bond position in the respective C33:1 isomer.

Determination of the signal peak isomers. Whereas all C33:2 co-elute to form a single peak, tritriacontene (C33:1) separates into two peaks with identical mass spectra in the GC-MS chromatogram, of which only the first (RI 3281, Supplementary Table S13) was found to be significantly upregulated in unpacked pupae by Pull et al. 201822. DMDS-derivatisation (Supplementary Table S12) and retention time comparison to the synthetic (Z)-10-C33:1 in the native chromatograms (Supplementary Fig. S6) revealed that this early C33:1 peak likely represents a mixture of isomers ranging from 13- to 9-C33:1. In contrast, the second, unaltered peak (RI 3289) is most plausibly attributed to the 7-C33:1 isomer. This assignment is supported by three lines of evidence: (i) in the derivatised data, the six identified isomers (Supplementary Fig. S4) eluted in order from 13 to 7, with the 7-isomer eluting distinctly after the 13- to 9-isomer cluster; (ii) overlay of the synthetic (Z)-10-C33:1 with the native extract revealed a shoulder indicating a residual compound trailing beyond the (Z)-10-C33:1 peak (Supplementary Fig. S6), suggesting that the first isomer cluster ends with the 9-isomer; and (iii) the relative abundance of the 7-isomer in the derivatised data (23% in non-signalling pupae and 18% in signalling pupae) closely matches the abundance of the second C33:1 peak in the non-derivatised data (21% in non-signalling and 16% in signalling pupae). The isomer ratio changes from the non-signalling to the signalling state (Supplementary Table S12) were therefore calculated based only on the 13- to 9-C33:1 isomers, as the 7-isomer is most likely not part of the biologically relevant pupal signal.

Abundance ratios of isomers in the signal peaks. The EIC- and SIM-abundances of the diagnostic ions (A)+ and (B)+ for DMDS-mono-adducts of the X-C33:1 isomers and (A)+ and (D)+ for DMDS-di-adducts of X,Y-C33:2 isomers were determined automatically (MassHunter), manually verified, and the integrations corrected, where necessary. We normalised the EIC abundance data for the (A)+ fragment of the eight C33:2-DMDS-di-adducts, as well as for the five C33:1-DMDS-mono-adducts of the 13- to 9-position isomers that we found to underlie the first C33:1 peak of average RI 3281 in the non-derivatised chromatogram, to the total sum of their respective (A)+ fragment abundances per extract. Specifically, for each adduct, its relative abundance was calculated by dividing its individual (A)+ fragment abundance by the sum of the (A)+ fragment abundances of either all C33:2-DMDS-di-adducts or the five C33:1-DMDS-mono-adducts of the RI 3281 cluster in its respective extract, yielding a normalised value between 0 and 1 for each adduct per extract, allowing us to assess the relative distribution of the C33:2 and C33:1 isomers for of the two signal peaks (C33:2 and C33:1 RI 3281) in both the signal and non-signal extract. Subsequently, these normalised isomer abundances in the signal extract were divided by the corresponding normalised abundances in the non-signal extract, receiving the isomer-specific ratios showing how strongly the isomer was up- resp. downregulated in signalling pupae (Supplementary Tables S11, S12).

Ordering details for used consumables can be found in Table S15.

Statistical data analysis
Statistical analyses were performed using R version 4.3.2 and RStudio version 2023.12.1.402. For all models, we checked the necessary assumptions by viewing histograms of data, plotting the distribution of model residuals, checking for unequal variances and the presence of multicollinearity and assessing models for influential observations. Where applicable, we transformed the data to obtain normality, using the package ‘bestNormalize’ (vs 1.9.1)71 (using either order-norm, standardised box-cox, log, square-root, Yeo-Johnson, or arcsinh transformations). For all models, we first tested the significance of the overall model compared to a null model (only including the intercept and variables for which we wanted to control) to test whether or not main effects or their interaction overall had a significant effect. For sampling time, we achieved balanced groups and higher statistical power by combining the time points 6-12 h to an early, 18–24 h to a middle and 30–42 h to a late ‘infection period’ in all analyses, except the time-resolved Cox Proportional Hazard Model. When both populations (Jena, Seva) were used in the experiment, we accounted for a population effect by including population as a control factor in the null model, since inclusion as a random effect would require at least five levels72. This was not required for the queen pupae, as they were only available from the Jena population. When multiple models were performed on related data, such as one model each for the four candidate peaks for both worker and queen pupae separately (Supplementary Tables S1a, b; S4a, b), or for the 14 non-candidate peaks of the queen pupae (Supplementary Table S6), we corrected at the model level (full-null model comparison) for multiple testing using the Benjamini-Hochberg procedure73 to protect against a false discovery rate (FDR) of 5%. When the overall model remained significant after correction for multiple testing, we proceeded to test the significance of interaction and, where applicable, the main effects, using likelihood ratio (LR) tests74 using the ‘lmtest’ package (vs 0.9.40)75. For models with significant interaction, the main effects cannot be reliably interpreted and are hence not reported. Within models, p-values of the interaction or main effects remained uncorrected, yet all post hoc comparisons were again corrected for multiple testing. Effect sizes were only calculated when a significant effect was found, using the packages ‘rstatix’ (vs 0.7.2)76 and ‘emmeans’ (vs 1.5.4)77. Unless otherwise stated, all reported p-values are two-sided, corrected for multiple testing where applicable and reported as exact values. Figures were created using R version 4.5.0 and RStudio version 2023.06.0.421 with packages ‘ggplot2’ (vs 3.5.2)78, ‘dplyr’ (vs 1.1.4)79, ‘ggpubr’ (0.6.0)80 and ‘Rmisc’ (vs 1.5.1)81.

Chemical profile. To determine whether the pupae-produced amounts of the four candidate CHCs identified by Pull et al. 201822 differed depending on infection status and presence/absence of workers – in particular, if the CHC abundances were different in infected pupae in the presence (I+W+) or absence (I+W-) of workers, and compared to the noninfected controls (I-W+, I-W-) – we ran a linear model per peak, testing for a significant interaction between our two main effects, thereby controlling for population (Jena, Seva) for the worker pupae and infection period (early, middle, late) for both worker and queen pupae by inclusion into the null model. Since we found no evidence of signalling in the four candidate peaks previously identified for worker pupae by Pull et al. 22 in the queen pupae (Supplementary Tables S4a, S5), we expanded our analysis in queen pupae to include the remaining 14 peaks (Supplementary Table S6).

Prior to statistical analysis, we obtained normality in the worker pupae by transforming all four candidate peaks by the ordered quantile normalisation. For the queen pupae, we had to used different transformations for different CHCs, i.e., box-cox transformation for C33:2, C33:1 (RI 3289), and 13MeC33, log transformation for 3MeC29, C30, C31, C33:1 (RI 3281) and 3MeC33, square root transformation for C35:2, ordered quantile normalisation for C27, C28, C29, C33+13MeC33:1, C34+14MeC34:1+12MeC34:1, C35:2+C35:1, C35+13MeC35:1, C37+13MeC37:1 and arcsinh transformation for 3MeC33:1.

As we found that signalling was restricted to the two immune-associated peaks (C33:2 and C33:1) in the worker pupae, we wanted to test whether the combined differences of these two signalling peaks would lead to a significantly different chemical profile of the infected pupae in worker presence (I+W+) to the other groups. To this end, we carried out a combined analysis aggregating C33:2 and C33:1 into one analysis after having z-transformed each compound separately. To obtain normality, worker pupae data were then transformed using the ordered quantile normalisation, and queen pupae data using the Yeo-Johnson transformation. We ran linear mixed models (LMM) using the ‘lme4’ package (vs 1.1.36)82 with the same variables as above variables, yet in addition accounting for peak (C33:2, C33:1) in the null model. We further included sample ID as a random effect to control for the non-independence of data points. After finding a significant interaction in the worker pupae (but no significance in the queen pupae, Supplementary Table S5), we carried out all-pairwise post hoc tests for the worker pupae (Supplementary Table S2) using the ‘emmeans’ package77. To determine if individual pupal infection load affected the pupal amount of the signalling peaks C33:2 and C33:1 in the worker pupae, we ran separate linear models (LM) for each peak, controlling for population, worker presence and infection period in the null model for the subset of the infected (I+) worker pupae (Supplementary Table S1b). We did the same analysis for the infected (I+) queen pupae for consistency, except here not having to control for population (Supplementary Table S4b).

Unpacking of pupae. Cox proportional-hazards regression analysis by use of the package ‘survival’ (vs 3.5.7)83 was used to determine, for both the worker and the queen pupae, whether unpacking occurred differently for the infected than the control pupae, again accounting for the ant population (Jena, Seva) in the worker pupae. We calculated the hazard ratio of how much more frequently unpacking occurred in the infected vs control pupae only for the worker pupae, as we found no significant difference in the queen pupae.

Immune gene expression. To test for the effect of infection and worker presence on pupal immune gene expression, we conducted separate linear models (LMs) for both castes and each immune gene (BGBP, PGRP-SC2, and Def1), after having achieved normality by ordered quantile normalisation. Since we found no significant interaction between infection and worker presence in either caste for any gene (Supplementary Tables S3, S8), we proceeded to test the significance of the two main effects. In all models, we controlled for the infection period, whereas we did not have to account for population, as only one population (Jena) was used. As the three genes did not differ in their expression pattern (worker pupae: Supplementary Table S3a, queen pupae: Supplementary Table S8a), we calculated the combined immunity value per pupa by averaging the z-transformed normalised expression values of the three genes. We then reran the above models for each caste (Supplementary Tables S3b, S8b).

To test for a possible difference in the overall immune investment between the castes either in the absence or presence of infection, we performed a combined z-transformation of all worker and queen pupae together, calculated the mean normalised gene expression per pupa as above and carried out Wilcoxon Rank-Sum tests to test for a different immune investment of the castes in (i) the absence (combined I-W- and I-W+) and (ii) the presence (combined I+W- and I+W+) of infection, and corrected for multiple testing.

Infection progression. To assess how pathogen load progressed over the course of infection for the pupae of both castes, we ran separate linear models (LMs) for worker and queen pupae, testing for the effect of infection period on the infection load. We controlled for worker presence in both worker and queen pupae models (Supplementary Tables S9a, b) and as above, for population in the model for the worker pupae only (Supplementary Table S9a). Following a significant interaction between infection period and load for both queen and worker pupae, we performed all-pairwise post hocs on whether the pupal infection loads differed between the early, middle and late stages of infection period using the ‘emmeans’ package (vs 1.10.0)77 (Supplementary Tables S9a, b). Prior to analysis, we obtained normality of the data distribution by transforming the data using the ordered quantile normalisation.

Worker reaction to extract application. To test whether the application of signal extract triggered higher unpacking of the otherwise healthy treated pupae than application of the non-signal extract, we ran separate binomial Generalised Linear Models (GLMs) with a binomial error distribution and a logit link function for worker and queen pupae. The response variable, unpacking, was modelled as a binary outcome, while extract type (signal vs non-signal) was included as the sole explanatory variable while controlling for experimental block, extract batch and in the case of worker pupae also population (Supplementary Table S10). We checked for overdispersion by comparing the ratio of residual deviance to degrees of freedom. We performed one-sided hypothesis tests, as we were specifically testing for an increase in unpacking when the extract came from signalling worker pupae.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The elegant study by Dawson is based on the interesting result that cuticular hydrocarbons (CHCs) of developing ants provide cues on their infection with a fungus that are perceived by adult ants that then destroy the pupae (Pull et al. 2018). Here, the authors report that these cues are active signals, leading to altruistic suicide, based their new results that the worker pupae only signal when adult workers are present and that the signals do not correlate with infection load. Furthermore, the authors show that the reproductive female caste, queens, do not change their CHCs and are simultaneously able to contain the fungus, even at higher infection doses. They also demonstrate that attending workers are not the source of these CHCs. Thus, they can conclude that the CHC changes are produced by the worker pupae. Unfortunately, I am not convinced that the results can rule out that the CHC changes are a passive consequence of the immune system of the ants. In fact, the authors make an argument that this could be the case by citing other studies. Immune system differences could also explain the lack of changes in queen pupae. Therefore, additional data on the immune system activity is needed in workers and queens under the experimental conditions to substantiate the claim that “infected ant pupae […] actively emit a chemical signal” (line 16). Hopefully, those samples are still available for such analyses. Even though this work is based on previously published identification of the CHC compounds tritriacontene and tritriadontadiene, these compounds are in need of a more accurate characterization to make comparisons to other studies (e.g., Wagoner et al. 2020) possible and allow exact replication of this study. Specifically, these compounds can occur in several isoforms (Pull et al. 2018 seem to have found two for tritriacontene) and I do not see which ones were studied here. Another methodological concern is the separate assessment of queen and worker pupae in 2019 and 2021 respectively. In addition, the queens stem only from one population, while workers from two populations were included. Otherwise, the manuscript is excellent and the study conducted quite well. The sample sizes are very good, the methods sophisticated and described thoroughly, the supplemental data are helpful, and the findings could certainly be very interesting and relevant. Minor comments: Line 33: Can you support this statement with a citation or two? Line 46: …increasing “its” own… ? Line 56: “if signaling promotes group health” should be listed as an independent factor because its sets apart cases of communicable vs. non-communicable diseases, which is significant. Line 73: Please write out the scientific names of these compounds. Caption of Figure 1A: To make it clearer, I would suggest “…as well as the pathogen free control pupae with (I-W+; dark pink) and without (I-W-) workers (Tables S1,S2).", "reviewer_2": "This is a nice study that tackles a fascinating topic: how species with complex social groups have evolved mechanisms for controlling infectious disease. The experiments here show that worker pupae emit two specific hydrocarbons when infected with a model pathogen, but only in the presence of adult workers who can respond to the signals. The response of workers to these signals is “unpacking” behavior, in which the (infected) developing pupae are removed from their pupal cases and destroyed. When adult workers are not present, the pupal signals are not evident. Queen pupae, who can more effectively fight off the infection, do not signal in this way. An especially nice component of this research is the use of isotopically-labeled worker hydrocarbons, which allowed the researchers to identify the source of the hydrocarbons, and exclude the possibility that workers were depositing the hydrocarbons on the pupae. The results here appear to provide confirmation of patterns seen in previous studies of both ants and honey bees. Although this work advances beyond what was previously reported in Pull et al (2018), there is also some overlap. Using the same experimental organisms and some of the same procedures, Pull et al reported (among other things) the unpacking of infected worker pupae by adult workers and the identity of four hydrocarbons that were correlated with this behavior, including the two implicated in this study. In this study, the authors have performed similar experiments, but have also added in the useful comparison to infected queen pupae, the isotopic clarification of the hydrocarbon origins. My biggest concern is the lack of a manipulative experiment showing the function of the dienes, C33:1 and C33:1. It should be straightforward to select uninfected worker pupae, treat some with these hydrocarbons (individually and in combination) and test whether this induces significantly higher unpacking behavior by the attendant workers (compared to control pupae who are treated with putative non-signaling hydrocarbons). Going even further, it would also be interesting to see if unpacking of queen pupae can be induced by addition of these hydrocarbons. More minor questions and comments: The procedure of exposure to Metarhizium, by rolling the pupae in a fungal suspension of the given concentration, would seem to add an extremely high dosage of spores. In addition, the post-exposure isolation for three days without the benefit of worker grooming would further intensify the exposure. How does this procedure reflect real-world exposures to pathogens? The authors describe exclusion of some replicates due to poor pupal or larval condition (e.g. damage, death, etc). These exclusions seem justified, but for transparency the authors should indicate the initial numbers and the numbers excluded for each reason in the supplementary material or online repository. Raw data and/or representative profiles from the GC-MS should be provided or archived in an available database. For the experiment in which sampling times were divided into early, middle, and late: why was the late period 12 hours long, versus six for the early and middle? Shouldn’t the late period be defined as the 30-36 hour period, not 30-42 hours?", "reviewer_3": "This work represents a nice and novel contribution to the field of socio-eco-immunology. The research combines molecular techniques, chemical analyses, immunological measurements and behavioral observations to decipher the role that ant pupae have on colony-wide disease resistance. Based on their data, we can now better visualize the nuanced dynamics between the different castes and different developmental stages within an ant colony. No longer can we assume that pupae in the social Hymenoptera represent an inactive and unresponsive developmental stage when its natal colony faces disease risks. I find this original work well conceived/planned, well analyzed and written. In particular, I find their methodology for disentangling the origin of cuticular hydrocarbons (either form the tending workers or from the worker-pupae or queen-pupae) ingenious. Using the 12C:13C ratio allowed the researchers to identify the origin of two immune-associated cuticular hydrocarbons C33:1 and C33:2 when ants are facing fungal infection. They established that C33:1 and C33:2 infected worker-pupae (which are less immunocompetent and have little future reproductive potential—as they are sterile when mature) produce distress hydrocarbons that elicit their destruction by the tending workers. In contrast, the fungal infected queen-pupae (which appear to have stronger immunocompetence that the worker-pupae and have high future reproductive potential) do not increase the production of these signals and therefore, are less likely to be targeted for destruction by the tending workers. This work merits to be published. Yet, I have a few suggestions that should probably be considered. 1) Overall, this work is well written. Yet, not all readers necessarily know much about ant biology. So additional basic information would be useful for those readers that are not experts in the field of social insect biology. Explaining that this ant species has a cocoon while other ant species do not (naked pupae) would be important. Furthermore, explain that the pupae developmental stage is solely dependent on workers, that it does not feed, that is immobile, that it transforms itself inside the cocoon from etc. This additional basic information would help the readers realize that in spite such characteristics, the pupae can still perceive the presence of fungal conidia, be immunocompetent and participate not only in chemical communication with adult nestmates but also exhibit altruistic behavior at this immature stage of development! And that is cool! 2) Page 2 lines 42-43: there is no citation for the vibratory displays in termites (Pathogen alarm responses by Rosengaus) or their heightened frequency of allogrooming behavior when exposed to Metarhizium (several articles by Rosengaus as well. • Rosengaus, R.B., Lefebvre, M.L., Jordan, C. and Traniello, J.F.A. (1999) Pathogen alarm behavior in a termite: A new form of communication in social insects. Naturwissenschaften, 86:544-548. • Rosengaus, R.B., Maxmen A.M., Coates, L.E. and Traniello, J.F.A. (1998) Disease resistance: a benefit of sociality in the dampwood termite Zootermopsis angusticollis (Isoptera: Termopsidae). Behavioral Ecology and Sociobiology, 44:125-134. • Rosengaus, R.B. and Traniello, J.F.A. (2001) Disease susceptibility and the adaptive nature of colony demography in the dampwood termite Zootermopsis angusticollis. Behavioral Ecology and Sociobiology, 50(6):546-556. 3) Page 4, line 87: be sure to explain that such chemicals are not being ingested by the pupae, but are just spread/shared through social interactions whenever the workers are grooming, moving the pupae around the nest etc.). Again, not everyone knows much about ant pupae and they may think you are referring to ingestion of the CHC? 4) Page 7, line 146: “feeble”??Perhaps a better descriptor would be “less immuno-competent”? 5) Page 7, line 150: perhaps add “destructive signaling”? 6) Page 8, line 174: as described, I immediately visualized this as a “naked pupae” species, only to later read that pupae in this species have a cocoon. Can you really see the eyes though the cocoon? 7) What are the different symptomologies as tie after exposure progresses in the pupae? Do you see any differences? What about the symptoms of disease for the tending ants? do they respond to the conidia on the pupae? I know the workers lick/groom the pupae more.. But do the grooming ants get infected themselves? What is their symptomatology? 8) Page 10; line 231: In what ways do they appear damaged or dead? How do you tell that pupae are dead if they are surrounded by a cocoon? 9) Throughout the ms: the authors use: “in dependence”. That is awkward. Perhaps replace that with “depending on” or “as a function of” 10) I believe the researchers were diligent in their conservative inclusion of data into their analyses. 11) Page 18, line 417: perhaps “chemical bouquet”? A pleasure reading your work.. [editorial note: reviewer name redacted]"}, "author_response": "Dear Editor, dear Reviewers, We would like to thank you for your thorough reviews and the detailed suggestions on how to improve our study. We have addressed all the points raised, as detailed below, and are pleased to submit a revised version of the manuscript that includes novel experiments and analyses. We believe that having examined the suggested points in greater detail has provided not only deeper insights into the interplay between individual immunity and chemical signalling in infected ant brood, and the chemical complexity of the signal itself, but also a clearer understanding of how disease detection and communication may have evolved across social insects. In the revised version, we provide all created data as source data with the manuscript and supplement. Thank you again for your time and efforts. With kind regards, Erika H. Dawson and Sylvia Cremer corresponding authors, on behalf of all authors REVIEWER COMMENTS Reviewer #1 (Remarks to the Author): The elegant study by Dawson is based on the interesting result that cuticular hydrocarbons (CHCs) of developing ants provide cues on their infection with a fungus that are perceived by adult ants that then destroy the pupae (Pull et al. 2018). Here, the authors report that these cues are active signals, leading to altruistic suicide, based their new results that the worker pupae only signal when adult workers are present and that the signals do not correlate with infection load. Furthermore, the authors show that the reproductive female caste, queens, do not change their CHCs and are simultaneously able to contain the fungus, even at higher infection doses. They also demonstrate that attending workers are not the source of these CHCs. Thus, they can conclude that the CHC changes are produced by the worker pupae. R1.1 Unfortunately, I am not convinced that the results can rule out that the CHC changes are a passive consequence of the immune system of the ants. In fact, the authors make an argument that this could be the case by citing other studies. Immune system differences could also explain the lack of changes in queen pupae. Therefore, additional data on the immune system activity is needed in workers and queens under the experimental conditions to substantiate the claim that “infected ant pupae […] actively emit a chemical signal” (line 16). Hopefully, those samples are still available for such analyses. We thank the reviewer for raising this point, as we agree that our previously provided data could not rule out that the presence of workers may have some influence on individual immunity, which could directly link to the changes in CHC profile. All the pupae in the CHC experiment were extracted for their DNA to obtain fungal infection load (qPCR of fungal DNA), hence immune gene expression analysis requiring RNA could not be obtained from the same samples. We would like to clarify that we had previously repeated the experiment with worker pupae to analyse the expression of three immune genes acting across different stages of the immune response. However, we did not include these data in the initial manuscript version, since they revealed no differences between pupae with and without workers in either the infected or control groups, which we considered a trivial finding at the time. It was only through the reviewer’s comment that we recognised the importance of these data in supporting our conclusions that the chemical profile of the ants is actively modulated by the ants themselves, rather than being a passive consequence of immune changes that might directly change their scent. This conclusion can be supported by the data, as the CHC profiles do not align with the gene expression patterns. Specifically, the chemical signal peaks were only upregulated in infected pupae with workers being present, whereas immune gene expression – consistently across all genes (see Fig. 1c & S3a, Table S3) – depended solely on infection status, showing no effect of worker presence/absence (lines 139-150). We have now repeated the experiment also for queen pupae and found the exact same immune gene expression pattern as in the worker pupae: an upregulation of immune gene expression upon infection, independent of worker presence or absence (Fig. 1d, S3b and Table S8). Again, these immunity data cannot explain the CHC patterns, which show no differences across the groups (lines 166-171). Therefore, analysis of physiological immunity of both castes revealed that the chemical signalling is not a mere representation of the immune state of the pupae, allowing us to conclude that the chemical signalling follows a mechanism independent of switching on the immune response. The reviewer’s suggestion to compare between castes revealed an additional important aspect: our data indicate that baseline immunity is higher in queen pupae (even independent of their larger body size, since immune gene expression values are normalised to a housekeeping gene), whereas worker pupae are able to reach similar expression levels upon infection. Previous work has shown that a high baseline immune investment is crucial for mounting a fast defence against pathogens, effectively reducing infection progression. This may explain why queen pupae are better able to control infection than worker pupae. Lastly, while it was known that social insect queens exhibit stronger physiological immunity than workers, this information was limited to adult stages. As also noted by Rev3, the fact that pupae can mount such responses during metamorphosis highlights another exciting finding of our study (lines 171-179). R1.2 Even though this work is based on previously published identification of the CHC compounds tritriacontene and tritriadontadiene, these compounds are in need of a more accurate characterization to make comparisons to other studies (e.g., Wagoner et al. 2020) possible and allow exact replication of this study. Specifically, these compounds can occur in several isoforms (Pull et al. 2018 seem to have found two for tritriacontene) and I do not see which ones were studied here. We appreciate this comment by the reviewer and have performed DMDS-derivatisation followed by isomer characterisation of the C33:2 and C33:1. This indeed gave very interesting additional insight, both in how the ants regulate their signalling and to which degree the chemical profiles of sick ants and bees can be compared. The reviewer is correct in pointing out that our native GC-MS chromatograms showed two separately eluting C33:1 peaks, one being upregulated in unpacked pupae, the other not (as already established in Pull et al eLife 2018). Previous work on Lasius neglectus adult workers (Cremer et al PLoS One 2008) had also described the presence of five C33:1 isomers and suggested the presence of several, still unidentified, C33:2 isomers. Our isomer analysis identified a total of eight C33:2 isomers and six C33:1 isomers being present in the pupal samples (Figs. S4,S5). We were excited to discover that one of the C33:1 isomers present in our ants – 10-C33:1 – which had previously been identified in honeybees where it is upregulated in sick brood, synthesized in its natural (Z)-configuration, and was found to trigger hygienic behaviour by the bees when applied in its pure form to healthy brood (Wagoner et al 2020). This isomer overlap between ants and bees allowed us to conclude that our isomers are also present in the (Z)-configuration. Even if this was already likely since the (Z)-configuration is the only reported stereoisomeric configuration of naturally-occurring insect CHCs, direct retention time overlap of the synthetic (Z)-10-C33:1 with our pupal extract (Fig. S6) confirmed this (lines 258-265). We also used the synthetic (Z)-10-C33:1 in our bioassay (see also response to Rev2), to test if it had a similar function in the ants as in honeybees, where it is an important indicator for viral infection and an elicitor of hygienic behaviour (Wagoner et al 2002). Yet, three lines of evidence suggest that this isomer does not play an important role in fungal disease signalling in ants: (i) application of the synthetic compound did not elicit pupal unpacking in our experiments (while natural extract transfers did, see below and Fig. 2), and (ii) (Z)-10-C33:1 was the isomer of the lowest abundance of C33:1 in the native GC-MS chromatograms, which (iii) did not differ in its relative proportion between signalling and non-signalling pupae (Table S12; lines 265-272). Interestingly, however, the two peaks (C33:2 and C33:1) differ in the way the signal is encoded: C33:2 is increased approx. 20 times in signalling pupae, with the eight isomers contributing in similar proportions throughout. C33:1, on the other hand, consists of six isomers, five of which co-elute in a cluster (13- to 9-C33:1), and the other as a separate peak (7-C33:1). These are in line with the first peak (RI 3279) being identified by Pull et al 2018 and confirmed in this study to be increased in overall abundance in the signalling pupae, and the second peak (RI 3288; Table S13), which is not upregulated in unpacked pupae). Interestingly, the most abundant compound of the unpacking-relevant cluster (12-C33:1) reduces drastically in signalling pupae, while two others (13- and 11-C33:1) double in their proportion. The remaining two (10- and 9-C33:1) don’t show any substantial changes. Since the overall abundance of the C33:1 isomer cluster is only 3-times higher in the signalling pupae, it seems like the main information here lies in the proportional change of the constituting isomers (lines 224-243). Therefore, as suggested by the reviewer, only the detailed analysis at the level of isomers allowed us to understand the complexity of the chemical signal and clearly revealed that ants and bees have not simply coopted the same compounds to be relevant disease cues or signals. Instead, the observed parallel evolution across social insect taxa reveals the importance of disease detection and colony-level defence lines in their colonies (lines 274-288). R1.3 Another methodological concern is the separate assessment of queen and worker pupae in 2019 and 2021 respectively. In addition, the queens stem only from one population, while workers from two populations were included. We are aware that it would have been optimal to also have been able to study the queen pupae from different populations, yet this was not possible due to sampling constraints. Whereas worker pupae are produced over a long period under summer conditions in the field and laboratory, queen pupae are only produced once a year in a single cohort, whilst they are only produced very rarely under laboratory conditions. For our experiments, we therefore relied on being able to collect queen pupae of the exact right stage in the field (not too far developed as otherwise they would be helped by the workers to exit their cocoons as part of normal hatching, whereas unpacking in the context of destructive disinfection occurs prematurely when pupae are not yet ready to hatch). This was only possible for the Jena population, where we also received support by a local ant group (Yuko Ulrich’s group) to detect the presence of the pupae and to collect them at the right stage. However, since Pull et al had already established that destructive disinfection is robust across populations of L. neglectus and even across species (L. niger), and because our new experiments further confirm this robustness across multiple years (Pull et al and this study, which now also includes multiple replicates over several years), we are confident in the generalisability of our findings across populations and time. R1.4 Otherwise, the manuscript is excellent and the study conducted quite well. The sample sizes are very good, the methods sophisticated and described thoroughly, the supplemental data are helpful, and the findings could certainly be very interesting and relevant. Thank you very much for this positive feedback on our work. R1.5 Minor comments: Line 33: Can you support this statement with a citation or two? We added Locatello et al 2013 and Gormally et al 2022 for the concealing on the infection state in other species (line 53). Line 46: …increasing “its” own… ? Added (line 66). Line 56: “if signaling promotes group health” should be listed as an independent factor because its sets apart cases of communicable vs. non-communicable diseases, which is significant. We now make this specific (lines 74/75). Line 73: Please write out the scientific names of these compounds. We added the UPAC names (lines 101/102). Caption of Figure 1A: To make it clearer, I would suggest “…as well as the pathogen free control pupae with (I-W+; dark pink) and without (I-W-) workers (Tables S1,S2). We clarified (line 1224). Reviewer #2 (Remarks to the Author): This is a nice study that tackles a fascinating topic: how species with complex social groups have evolved mechanisms for controlling infectious disease. The experiments here show that worker pupae emit two specific hydrocarbons when infected with a model pathogen, but only in the presence of adult workers who can respond to the signals. The response of workers to these signals is “unpacking” behavior, in which the (infected) developing pupae are removed from their pupal cases and destroyed. When adult workers are not present, the pupal signals are not evident. Queen pupae, who can more effectively fight off the infection, do not signal in this way. An especially nice component of this research is the use of isotopically-labeled worker hydrocarbons, which allowed the researchers to identify the source of the hydrocarbons, and exclude the possibility that workers were depositing the hydrocarbons on the pupae. The results here appear to provide confirmation of patterns seen in previous studies of both ants and honey bees. Although this work advances beyond what was previously reported in Pull et al (2018), there is also some overlap. Using the same experimental organisms and some of the same procedures, Pull et al reported (among other things) the unpacking of infected worker pupae by adult workers and the identity of four hydrocarbons that were correlated with this behavior, including the two implicated in this study. In this study, the authors have performed similar experiments, but have also added in the useful comparison to infected queen pupae, the isotopic clarification of the hydrocarbon origins. R2.1 My biggest concern is the lack of a manipulative experiment showing the function of the dienes, C33:1 and C33:1. It should be straightforward to select uninfected worker pupae, treat some with these hydrocarbons (individually and in combination) and test whether this induces significantly higher unpacking behavior by the attendant workers (compared to control pupae who are treated with putative non-signaling hydrocarbons). Going even further, it would also be interesting to see if unpacking of queen pupae can be induced by addition of these hydrocarbons. We agree with the reviewer that the evidence provided in the first submission was only correlational, and that manipulative experiments are required to establish a causal relationship. We therefore developed a bioassay in which we experimentally transferred the CHC extracts of signalling worker pupae, as well as that of non-signalling worker pupae as a control onto healthy worker pupae and queen pupae. This allowed us to test whether transfer of the chemical signal alone was sufficient to induce unpacking by the workers. Indeed, application of signal extract induced unpacking, which was not only true for receiving healthy worker pupae (Fig. 2a, lines 201-207), but even when the extract from the signalling worker pupae was transferred between castes, to the queen pupae (Fig. 2b, lines 207-210). We further show that our procedure by itself was not eliciting any unpacking (application of solvent only, line 746 ff), and that the transfer of non-signal extract only elicited little worker unpacking (Figs. 2a,b). We can therefore conclude that it is the change in the chemical signatures from non-signalling to signalling pupae (visualised in Figs. 2c.d) that by itself leads to trigger unpacking. We are aware that this change constitutes a change in CHC blend and also recognise the reviewer’s further suggestion to test the effects of the signal CHCs not only in combination as they occur in the natural extracts, but also separately. However, our detailed analysis of the C33:2 and C33:1 peaks revealed the existence of at least 14 different isomers of the two CHCs, which show a complex pattern of up- or downregulation in their relative proportions (see detailed in our response to R1.2). Reconstructing and applying synthetic blends that accurately reproduce the diversity of isomers and the change of their relative abundances of such complexity as observed in our natural signal profiles would be technically extremely challenging and beyond the scope of the current study, especially since the synthesis of alkadienes can involve highly demanding analytical chemistry. Moreover, the observed complexity in the C33:2 and C33:1 patterns is consistent with findings in other recognition systems of social insects, which often rely on diverse compound ratios rather than single-molecule abundances. Therefore, targeted manipulation of individual isomers on their own may not be straightforward to enable us to get a more detailed insight into the biological nature of the signal given the natural profiles change in 20-fold upregulation of our eight C33:2 isomers (in equal proportion) and the 3-fold overall abundance increase with changing isomer ratios in at least 3 abundant isomers. Overall, our experiments revealed that the change in chemical blend alone is sufficient to trigger unpacking, and that the workers would react to similar changes also in the queen pupae, in case they would produce them. R2.2 More minor questions and comments: The procedure of exposure to Metarhizium, by rolling the pupae in a fungal suspension of the given concentration, would seem to add an extremely high dosage of spores. In addition, the post-exposure isolation for three days without the benefit of worker grooming would further intensify the exposure. How does this procedure reflect real-world exposures to pathogens? In Pull et al. 2018, we quantified by use of quantitative real time PCR targeting the fungal DNA, that the application dose of 1 µl of a 1 x 106 spores/ml fungal suspension results in approx. 1800 spores attaching to the pupal cocoon of a worker pupae, of which 95 spores reach the pupa inside the cocoon, where contact with the cuticle induces germination as the first step of infection. Here, we used the same dose for the worker pupae, but exposed the queens to a higher load, which we inferred to lead to an approximate load of 940 spores reaching a queen pupa (lines 355-358). This higher dose was chosen because queen pupae are of much larger size than worker pupae and preliminary work showed that an approx. half of this dose was insufficient to successfully induce an infection in the queen pupae (lines 364/365). Like other entomopathogenic fungi, Metarhizium spores are highly abundant in nature: single cadavers show outgrowth of spore packages making up to 12 million spores and soil can contain 5000 spores / gram soil (lines 358-360). Therefore, we consider our exposure doses to be within natural range. To standardise our experimental procedures and ensure a high probability of infection, we introduced an isolation step to prevent workers from grooming off the spores after application. Yet, we would like to emphasise that destructive disinfection itself does not rely on this experimental setup as shown in Fig. 1a of Pull et al 2018. Importantly, L. neglectus naturally separates its brood according to developmental stage, creating brood chambers that consist exclusively of pupae, separate from larval chambers. Reflecting the reduced care requirement of the pupae (i.e. pupae are not fed, unlike larvae), we also generally observe fewer workers present in these pupal chambers in our stock colonies. While our three-day isolation may not precisely replicate nest conditions, we do not consider it to introduce an unrealistic scenario. More broadly, the fact that destructive disinfection has evolved as a targeted response to fungal infection suggests that established infections in pupae must occur with sufficient frequency under natural conditions to impose selective pressure. Given the ants build their nests in the soil, which is rich in infectious stages of entomopathogens (see above), exposure of the brood is likely to occur frequently. While such early-stage pathogen exposures are likely often removed through allogrooming before they can progress, it follows that grooming is not always successful or fast enough, allowing infections to occasionally establish and trigger the destructive disinfection response. Thus, our use of isolation served to standardise infection success under experimental conditions, but does not undermine the ecological or evolutionary relevance of destructive disinfection. R2.3 The authors describe exclusion of some replicates due to poor pupal or larval condition (e.g. damage, death, etc). These exclusions seem justified, but for transparency the authors should indicate the initial numbers and the numbers excluded for each reason in the supplementary material or online repository. We now provide all these numbers in the respective methods sections (CHC and infection progression experiment, lines 390-400; immune gene experiment, lines 589-92; bioassay, lines 713-14) and in the data exclusion section of the reporting summary. R2.4 Raw data and/or representative profiles from the GC-MS should be provided or archived in an available database. We have now included representative chromatograms of the signalling vs non-signalling extracts in the new main Fig. 2c,d, as well as in Suppl. Fig. S6. We also provide the isomer structures in Suppl. Fig. S4, their mass spectra in Suppl. Fig. S5, the and the isomer ratios in Suppl. Tables S11 and S12. Our source data further provide the pupal relative peak abundances for all 18 analysed peaks for each pupa, as well as the EIC abundances of all C33:2 and C33:1 isomers. R2.5 For the experiment in which sampling times were divided into early, middle, and late: why was the late period 12 hours long, versus six for the early and middle? Shouldn’t the late period be defined as the 30-36 hour period, not 30-42 hours? Most unpacking occurs at time points 12 and 18 hours, so that these time points received higher sampling effort than the later time points, when unpacking becomes rarer. Therefore, to balance our sample sizes and ensure higher statistical power, we combined the last three sampling time points to a single late period (lines 891-94). Reviewer #3 (Remarks to the Author): This work represents a nice and novel contribution to the field of socio-eco-immunology. The research combines molecular techniques, chemical analyses, immunological measurements and behavioral observations to decipher the role that ant pupae have on colony-wide disease resistance. Based on their data, we can now better visualize the nuanced dynamics between the different castes and different developmental stages within an ant colony. No longer can we assume that pupae in the social Hymenoptera represent an inactive and unresponsive developmental stage when its natal colony faces disease risks. I find this original work well conceived/planned, well analyzed and written. In particular, I find their methodology for disentangling the origin of cuticular hydrocarbons (either form the tending workers or from the worker-pupae or queen-pupae) ingenious. Using the 12C:13C ratio allowed the researchers to identify the origin of two immune-associated cuticular hydrocarbons C33:1 and C33:2 when ants are facing fungal infection. They established that C33:1 and C33:2 infected worker-pupae (which are less immunocompetent and have little future reproductive potential—as they are sterile when mature) produce distress hydrocarbons that elicit their destruction by the tending workers. In contrast, the fungal infected queen-pupae (which appear to have stronger immunocompetence that the worker-pupae and have high future reproductive potential) do not increase the production of these signals and therefore, are less likely to be targeted for destruction by the tending workers. This work merits to be published. Yet, I have a few suggestions that should probably be considered. R3.1 1) Overall, this work is well written. Yet, not all readers necessarily know much about ant biology. So additional basic information would be useful for those readers that are not experts in the field of social insect biology. Explaining that this ant species has a cocoon while other ant species do not (naked pupae) would be important. Furthermore, explain that the pupae developmental stage is solely dependent on workers, that it does not feed, that is immobile, that it transforms itself inside the cocoon from etc. This additional basic information would help the readers realize that in spite such characteristics, the pupae can still perceive the presence of fungal conidia, be immunocompetent and participate not only in chemical communication with adult nestmates but also exhibit altruistic behavior at this immature stage of development! And that is cool Thank you for pointing this out. We have added this basic information in the introduction (lines 93 ff), as well as in the Results section, where we now also discuss our new analyses of the pupal immune genes (lines 174-77). We agree that it may not be expected from an organism undergoing metamorphosis to have such fine-tuned responses. R3.2 2) Page 2 lines 42-43: there is no citation for the vibratory displays in termites (Pathogen alarm responses by Rosengaus) or their heightened frequency of allogrooming behavior when exposed to Metarhizium (several articles by Rosengaus as well. • Rosengaus, R.B., Lefebvre, M.L., Jordan, C. and Traniello, J.F.A. (1999) Pathogen alarm behavior in a termite: A new form of communication in social insects. Naturwissenschaften, 86:544-548. • Rosengaus, R.B., Maxmen A.M., Coates, L.E. and Traniello, J.F.A. (1998) Disease resistance: a benefit of sociality in the dampwood termite Zootermopsis angusticollis (Isoptera: Termopsidae). Behavioral Ecology and Sociobiology, 44:125-134. • Rosengaus, R.B. and Traniello, J.F.A. (2001) Disease susceptibility and the adaptive nature of colony demography in the dampwood termite Zootermopsis angusticollis. Behavioral Ecology and Sociobiology, 50(6):546-556. We are sorry for our confusing referencing. We had previously only cited the connection of the vibratory signal to grooming providing a reference at the very end of the sentence, intermingled with the wound care in ants. We now provide a reference describing the vibrational signal and one revealing its grooming-inducing effect on nestmate termites, and cite the references throughout the text for clarity (lines 62-64). R3.3 3) Page 4, line 87: be sure to explain that such chemicals are not being ingested by the pupae, but are just spread/shared through social interactions whenever the workers are grooming, moving the pupae around the nest etc.). Again, not everyone knows much about ant pupae and they may think you are referring to ingestion of the CHC? In addition to now spelling out that the pupae do not engage in feeding (lines 117, 174-77), we have now specified that we needed to exclude external transfer by grooming (lines 115-120). We also extended this sentence to mention that the pupal and adult CHC profiles overlap and referenced the according publications. R3.4 4) Page 7, line 146: “feeble”??Perhaps a better descriptor would be “less immuno-competent”? We have exchanged the “feebler worker immune system” by “less potent” and contrast it to a “stronger” queen immune system (lines 189-90). R3.5 5) Page 7, line 150: perhaps add “destructive signaling”? We have expanded to “signalling for own destruction” (line 194). R3.6 6) Page 8, line 174: as described, I immediately visualized this as a “naked pupae” species, only to later read that pupae in this species have a cocoon. Can you really see the eyes though the cocoon? Yes, the eyes and mandibles are visible through the worker cocoon, with some magnification, as shown in the below photograph that was taken by my previous PhD student CD Pull, contrasting a pupa with and one with removed cocoon. We determine the stage of each worker pupae before the experiment by use of a stereoscope, as it is crucial for our experiments that the pupae have not yet completed their metamorphosis to become young hatching workers (callows) during the whole period of the experiment (3 days of incubation and up to 42 h in the experiment). Natural hatching would interfere with our destructive disinfection unpacking observations, as the workers also support the pupae from leaving the cocoon then, but, if it occurs, it can easily be disentangled as those then emerge as walking adults. For the queen pupae, however, the cocoon is not transparent and we need to rely on a comparative approach here as all queen pupae produced in a colony at a time belong to the same age cohort, so that opening some queen cocoons gives us a very good estimate for the remaining pupae. We now explain in the manuscript (lines 324-3277): “Experiments were performed with pupae of a standardised developmental stage (white pupae with black eyes, as visible through the cocoon using a stereoscope (Leica S6 E) for worker pupae; for queen pupae, the stage can be reliable inferred by checking some pupae in the colony, as they develop highly synchronised in same-age cohorts).” Photo C D Pull. Arrow towards the eye that is visible through the cocoon. R3.7 7) What are the different symptomologies as tie after exposure progresses in the pupae? Do you see any differences? What about the symptoms of disease for the tending ants? do they respond to the conidia on the pupae? I know the workers lick/groom the pupae more.. But do the grooming ants get infected themselves? What is their symptomatology? Thank you for pointing this out. After exposure to the fungal conidiospores (referred to “spores” throughout), it takes some time for the spores to germinate, form an appressorium, and penetrate the host cuticle. Once internal infection is established, spores are no longer externally transmissible. During the following days of internal infection, the pathogen replicates inside the host and kills it. Infectiousness resumes only after host death, when hyphae emerge and sporulation begins. In Pull et al 2018, we showed that destructive disinfection occurs before this infectious stage, posing no risk to workers. We have clarified this in the manuscript (lines 97-99): “Notably, this destructive disinfection is performed by the workers during the non-infectious incubation period of the fungal pathogen, therefore not inducing any disease-risk to the workers.” R3.8 8) Page 10; line 231: In what ways do they appear damaged or dead? How do you tell that pupae are dead if they are surrounded by a cocoon? As seen in the above photograph, the cocoon allows partial visual inspection of the pupa inside, and dead pupae often show a change in colouration. In addition, the cocoon itself becomes less oval and takes on a ‘shrivelled’ appearance. We now describe this in the manuscript as: “as identified by a ‘shrivelled’ morphology or a change in colouration” (lines 390-92). To ensure that we analysed only actively signalling individuals, we conservatively excluded any brood showing signs of impairment or death. R3.9 9) Throughout the ms: the authors use: “in dependence”. That is awkward. Perhaps replace that with “depending on” or “as a function of” We have changed this throughout. R3.10 10) I believe the researchers were diligent in their conservative inclusion of data into their analyses. Thank you. R3.11 11) Page 18, line 417: perhaps “chemical bouquet”? Changed (line 574). A pleasure reading your work.. [editorial note: reviewer name redacted] We would like to thank all reviewers again for their careful assessment of our work and the detailed suggestions for improvement."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I would like to congratulate the authors for the very thorough revision, which included additional data that addressed all my concerns.", "reviewer_2": "I was happy to see this revised version of the previous manuscript. I appreciate that the authors addressed the major criticisms from the previous review, both mine and those of the other reviewers. The clarifications and added experiments significantly improve and strengthen this study, and I have no additional major comments. This is really a fascinating system and I look forward to seeing continue research along these lines in this and other model systems. Minor comments: Line 50 – “aggressed” is a bit awkward. Better to say “attacked” or “subjected to aggression by”. Line 122 – Better to say “before the experiment” rather than “ahead of the experiment”. Line 174 – Change “where, as previously shown” to “when, as previously shown”. (and remove comma before “where”). Use of commas is inconsistent throughout and would benefit from input from style editor."}, "author_response": "POINT-BY-POINT RESPONSE REVIEWERS' COMMENTS Reviewer #1 (Remarks to the Author): I would like to congratulate the authors for the very thorough revision, which included additional data that addressed all my concerns. Thank you very much. Reviewer #2 (Remarks to the Author): I was happy to see this revised version of the previous manuscript. I appreciate that the authors addressed the major criticisms from the previous review, both mine and those of the other reviewers. The clarifications and added experiments significantly improve and strengthen this study, and I have no additional major comments. This is really a fascinating system and I look forward to seeing continue research along these lines in this and other model systems. Thank you very much. Minor comments: Line 50 – “aggressed” is a bit awkward. Better to say “attacked” or “subjected to aggression by”. Changed to the laCer. Line 122 – Better to say “before the experiment” rather than “ahead of the experiment”. Changed (now line 123). Line 174 – Change “where, as previously shown” to “when, as previously shown”. (and remove comma before “where”). Changed (now line 176). Use of commas is inconsistent throughout and would benefit from input from style editor. We have used the commas the best we could and would be very happy to follow the changes suggested by the style editor."}]

Decision letter