Volatile and non-volatile pathogen cues shape host extracellular vesicles production in pre-infection response

Domain: chemistry
Published: 2025-12-21
Editorial outcome: major_revision

Abstract
In natural environments, animals encounter pathogen-derived chemicals long before infection occurs. How such anticipatory cues influence extracellular vesicle (EV) dynamics, which are central to immune regulation, intercellular communication, and stress responses, remains unknown. Using Caenorhabditis elegans, we show that pathogen-derived volatile and non-volatile compounds trigger distinct EV pathways through separate sensory and molecular mechanisms. Non-volatile secretome components, including the tripeptide Ile-Pro-Pro, activate immune-dependent EV production, whereas volatile metabolites elicit immunity-independent EV formation. Both responses require sensory input from ASK, ADL, and AWC neurons and converge on a neural circuit involving RMG, AIB, and AIA interneurons. GPCRs SRI-19, SRI-36/39, and SRR-6 mediate non-volatile responses, with SRR-6 acting in the intestine to regulate muscle EVs release. Notably, pre-exposure to pathogen volatiles enhances offspring survival during subsequent infection in an SRI-19–dependent manner, suggesting a predictive, intergenerational benefit of pathogen detection. In summary, our findings uncover that pathogen-derived chemical cues shape host EV production via specialized sensory circuits, revealing how animals anticipate infection and prime protective physiological responses.

Introduction
Extracellular vesicles (EVs), including exosomes and microvesicles, are pivotal in the host immune response by mediating intercellular communication and regulating immune functions. Released by various cell types, EVs carry a diverse array of bioactive molecules such as antigens, signalling molecules, and genetic material, thus influencing immune cell behavior and activity1,2. Pathogen-derived EVs often contain pathogen-associated molecular patterns (PAMPs) that can activate immune responses3, while host-derived EVs help modulate inflammation and immune activation, maintaining homeostasis and enhancing defense mechanisms against pathogens4. These roles for EVs have been well-documented during active infection, where pathogens are already invading the host. However, pathogens release both volatile and non-volatile compounds, which can alert and prepare the host to their exposure5–7. Whether such compounds can modulate EV production prior to infection is not known.

The nematode Caenorhabditis elegans is a widely used model for studying host-pathogen interactions, particularly valuable for examining its responses to clinically significant human pathogens such as Pseudomonas aeruginosa, Serratia marcescens, and Staphylococcus aureus8. This organism offers several advantages due to its simplicity, genetic tractability, and well-characterized immune responses. C. elegans relies solely on innate immune pathways, making it an ideal organism for dissecting fundamental aspects of innate immunity without the confounding influence of an adaptive immune system9,10. Additionally, its short lifespan and large brood size enable high-throughput genetic and pharmacological screens11. The evolutionary conservation of many immune pathways between C. elegans and higher organisms further enhances its relevance for studying host-pathogen interactions12,13. Moreover, C. elegans uses specialised G protein-coupled receptor (GPCR)-mediated sensory circuits to detect environmental pathogens and orchestrates systemic outputs, including immune activation and behavioral avoidance, in response to microbial metabolites such as phenazine-1-carboxamide, pyochelin14, and volatile 1-undecene15.

C. elegans has also emerged as a valuable model for studying EV production. Due to its transparent body and well-characterized genetics, C. elegans allow tracking of EV production in real-time and investigation of the regulatory pathways involved16. One example of an evolutionarily conserved class of particularly large EVs that is investigated in worms are exophers. Exophers have been shown to be involved in waste removal and material exchange between tissues, with key functions in cellular stress responses, tissue maintenance, and reproduction17–22. Previous studies have demonstrated that exophers help protect neuronal activity in C. elegans by expelling toxic cellular debris17, a process also observed in mammals, where mouse cardiomyocytes release exophers to discard defective mitochondria, maintaining metabolic balance and preventing inflammation23. In addition to waste disposal, we previously demonstrated that exophers facilitate inter-tissue material transfer to support reproductive fitness18, under the control of social cues originating from other individuals in the population22.

In this context, we aimed to investigate whether EV production in a host organism can be modulated by the mere presence of pathogens in the environment. Importantly, we focused on the response to pathogen volatile and non-volatile secretomes, allowing us to decouple this regulation from direct infection-related responses. Using exophers released by C. elegans body wall muscles as a model, we sought to explore the molecular mechanisms underlying pathogen secretomes-induced EV dynamics.

Results
Infection with pathogens induces exopher production in hermaphrodite muscles
To test whether pathogen infection influences the production of EVs (exophers) in C. elegans (Fig. 1a), we exposed worms at adulthood day 1 to live Pseudomonas aeruginosa PA14 or Serratia marcescens Db10 bacteria for 3 hours. Next, we moved them back to plates seeded with a non-pathogenic Escherichia coli OP50 bacteria and, 24 hours later, we quantified the number of exophers released by body-wall muscle cells (BWMs) following a previously described methodology24 (Fig. 1b). Our results show that worms exposed to both types of pathogenic bacteria produce significantly more exophers than worms that were kept on E. coli OP50 bacteria throughout the whole experiment (Fig. 1c).

Given that extracellular vesicles in other organisms are often part of the immune response1,25, we next examined whether basal production of exophers as well as increased exopher production upon exposure to pathogenic bacteria depends on specific immune pathways. We tested various mutants deficient in key nematode immune response pathways10,26, including the insulin pathway (akt-1, daf-16)27, TGF-β pathway (dbl-1)28, p38 MAPK pathway (tir-1, pmk-1)29,30, and Intracellular Pathogen Response (IPR) pathway (cul-6)31,32 (Fig. 1d). In some of the tested immune response pathways, we observed altered levels of exophergenesis, either decreased or increased, compared to wild-type worms. This was observed under standard growing conditions on non-pathogenic E. coli OP50 bacteria after knocking out at least one component of each pathway (Fig. 1e). Surprisingly, despite their altered basal levels, most of the tested mutants still exhibited a robust, statistically significant increase in exopher production upon pathogen exposure (Fig. 1f-h). The sole exception was the cul-6 mutant with a compromised IPR pathway, which showed an increase in exopher production upon exposure to P. aeruginosa and a decrease in exopher production upon exposure to S. marcescens when compared to the control (Fig. 1i). Among the immune-deficient strains we tested, the magnitude of pathogen-induced exopher upregulation differed. Following P. aeruginosa exposure, the dbl‑1, pmk‑1, and cul‑6 mutants exhibited increases in exopher production comparable to wild‑type levels, whereas tir‑1 mutants showed an even greater induction. In contrast, daf‑16 mutants displayed a significantly diminished response relative to wild‑type, while akt‑1 mutants, defective in the negative regulator of DAF‑16, exhibited an exaggerated increase (Supplementary Fig. 1a). Because AKT‑1 inhibits DAF‑16 in the insulin pathway, these data indicate that although exopher induction by pathogen presence is broadly robust, its amplitude is fine-tuned by DAF‑16-dependent transcriptional programs as well as by p38 MAPK pathway. A similar pattern emerged when worms were challenged with S. marcescens, with the exception that tir‑1 mutants responded like wild‑type and cul‑6 mutants showed a significant reduction in exopher induction (Supplementary Fig. 1b).

Collectively, these results indicate that exopher upregulation in response to pathogens is not driven by a single canonical immune pathway but is primarily modulated through the insulin/DAF-16 axis, with other pathways contributing in a minor or compensatory manner.

Previous work has established that exopher biogenesis requires fertility and the presence of embryos in the uterus18,33. To determine whether pathogen exposure alone can bypass this requirement, we exposed sterile, FUdR-treated worms to P. aeruginosa and S. marcescens. In both cases, sterile animals failed to produce exophers (Supplementary Fig. 1c), demonstrating that fertility remains a prerequisite for pathogen‑induced exophergenesis. When we examined embryo accumulation, S. marcescens exposure led to an increase in uterine embryos, whereas P. aeruginosa-exposed worms showed no change in embryo accumulation (Fig. 1j). Therefore, although both pathogens stimulate exopher production in fertile animals, only S. marcescens does so alongside embryo accumulation. This observation is critically important, as it shows that P. aeruginosa activates exophergenesis through a novel signalling pathway that is independent of the classic mechanism linked to embryo accumulation. This model allows for the isolation and study of the direct response to a pathogenic signal without the confounding influence of maternal signals. For this reason, we decided to focus our subsequent mechanistic analyses specifically on exophergenesis induced by P. aeruginosa.

Pathogen non-volatile and volatile secretomes trigger exopher production
Recent reports indicate that C. elegans can sense pathogen-derived volatile metabolites (airborne compounds emitted by the pathogen), which influence their physiology in a cell non-autonomous manner15,34. Previous studies have also shown that exposing C. elegans to the P. aeruginosa secretome (the full complement of water‑soluble factors present in clarified culture supernatant including small metabolites, peptides, proteins, and EVs) leads to a robust immune response35. We hence aimed to determine whether the increased production of EVs in response to pathogens requires direct infection or can be triggered simply by exposure to volatile or soluble bacterial components.

We first investigated whether exposure to pathogen odours alone would be sufficient to induce exopher production in muscle cells. To test this, we covered an NGM plate seeded with OP50 and containing age-synchronized L4-stage worms with another NGM plate containing P. aeruginosa and sealed both plates together with parafilm. Worms were incubated in this setup for 48 hours until they reached adulthood day 2, after which exophers were counted (Fig. 2a). Our results demonstrate that exposure to P. aeruginosa volatile metabolites indeed induces exopher production (Fig. 2b and c) and causes a slight embryo accumulation in utero (Fig. 2d).

Second, we aimed to determine whether the increased production of EVs in response to pathogens is triggered by exposure to the bacterial non-volatile secretome (Fig. 2e). As shown in Fig. 2f and g, direct infection with P. aeruginosa is not necessary; worms grown on plates with P. aeruginosa secretome also produced more exophers. Notably, this increase in exopher production is not associated with increased embryo accumulation in the worm’s uterus (Fig. 2h). The fact that P. aeruginosa non-volatile secretome fails to increase embryo accumulation in utero, in contrast to the retention induced by volatile metabolites, suggests that non‑volatile pathogen cues may actively suppress the embryo‑accumulation response typically triggered by volatiles. This opposing outcome points to distinct downstream signalling branches that modulate reproductive physiology in response to different classes of pathogen‑derived compounds. This also aligns with our observation that simultaneous exposure to volatile metabolites and the non-volatile secretome is non-additive for exopher production (Fig. 2i).

Consistent with previous results, FUdR-sterilized worms failed to upregulate exopher production in response to either P. aeruginosa volatile metabolites or non-volatile secretome (Supplementary Fig. 2a and d). This demonstrates that fertility is essential for exopher upregulation by both volatile and non‑volatile pathogen cues. Moreover, because starvation alone is sufficient to increase exopher production18,21, we monitored pharyngeal pumping to rule out reduced feeding as a confounding factor. We found no significant change in pumping rates following exposure to either pathogen volatile metabolites or non-volatile secretome (Supplementary Fig. 2b and e), confirming that the observed exopher upregulation is not driven by altered food intake.

We further explored whether neuronal exophers, previously shown to help maintain proteostasis in neurons, are similarly regulated by the pathogen-derived secretome. Using a touch-receptor neuron reporter strain17, we exposed animals to either volatile metabolites or non-volatile P. aeruginosa secretome as described above and quantified neuronal exophers. Strikingly, we found that volatile metabolites, but not non-volatile secretome, significantly upregulate exopher formation in neurons (Supplementary Fig. 2c and f), indicating that the signalling machinery controlling EV production differs between muscle and neuronal cells.

Volatile and non-volatile cues engage distinct immune-regulatory mechanisms
Next, we investigated whether the increased muscle exopher production in our new experimental setups is influenced by innate immunity signalling pathways. We first assessed each immune response mutant against its own unexposed baseline and then compared the magnitude of P. aeruginosa‑induced changes to wild‑type responses. On one hand, our data show that insulin, TGF-β, p38 MAPK, and IPR pathways are not individually required for the robust increase in exopher production triggered by volatile metabolites as each mutant mirrored wild‑type induction (Fig. 3a and c), although we cannot exclude the possibility of redundant or compensatory interactions. However, there is a notable discrepancy in the role of these pathways when considering the non-volatile secretome-dependent increase in EV production. Specifically, while the insulin pathway does not by itself appear to be involved, the TGF-β, IPR, and partially p38 MAPK pathways are essential for the non-volatile secretome-dependent increase in exopher production (Fig. 3b and c). On the other hand, comparison of mutant versus wild-type animals showed that pmk-1 and akt‑1 mutants displayed an even greater increase in exophers than wild-type upon volatile metabolites and non-volatile secretome exposure, while dbl-1 mutants exhibited a blunted response to both types of compounds (Supplementary Fig. 3a and b). Together, these results indicate that C. elegans relies on distinct immune signalling mechanisms for EV production depending on the chemical nature of the stimulus: volatile P. aeruginosa metabolites trigger exophergenesis that is independent of multiple pathways yet quantitatively fine‑tuned by insulin, TGF-β, and p38 MAPK signalling, whereas non‑volatile secretome‑driven upregulation requires TGF-β, IPR, and partially p38 MAPK pathways.

Tripeptide Ile-Pro-Pro present in P. aeruginosa non-volatile secretome upregulates exopher production
During the course of our study, we observed a sudden decline in the reliability of our non-volatile secretome-based exopher upregulation assay. Troubleshooting traced this inconsistency to a switch in the membrane filters used for supernatant clarification. We confirmed this by testing five different filter types (two previously used and three additional ones) and found that only two permitted robust exopher induction (Fig. 4a). We leveraged this filter sensitivity as a bioassay to pinpoint the active component(s) in P. aeruginosa supernatant (Fig. 4b). Using liquid chromatography–mass spectrometry, we compared the metabolite profiles of exopher-inducing versus non-inducing filtrates from the same bacterial liquid culture and identified 65 statistically significant, differentially abundant compounds (Supplementary Data 1). Interestingly, the active supernatant was enriched in several small peptides, dipeptides, tripeptides, and tetrapeptides, all of which contained at least one proline residue. Moreover, inspired by previous work demonstrating that N,N-dimethyltryptophan–containing dipeptide can modulate C. elegans physiology, we selected Ile-Pro-Pro (Fig. 4c), a tripeptide known to be produced by lactic acid bacteria36, for functional testing.

When synthetic Ile-Pro-Pro was added to standard NGM medium, exopher production increased in a dose-dependent manner (Fig. 4d). At 50 µM, we observed a 17% rise over vehicle control, rising to 29% increase at 100 µM. These results identify the tripeptide Ile-Pro-Pro as a specific, pathogen-associated molecule capable of inducing exopher production in the host. While likely acting in concert with other secreted factors, Ile-Pro-Pro represents a key molecular signal through which C. elegans can sense the metabolic state of surrounding bacteria.

Multiple types of sensory neurons regulate exopher production in response to pathogen secretome
Olfactory neurons in C. elegans detect numerous environmental signals that influence various aspects of the worm’s life, including behavior, physiology, and reproduction37. Additionally, our recent findings have shown that olfactory neurons regulate pheromone-dependent increases in EV production22. To identify the sensory neurons responsible for regulating the pathogen non-volatile secretome-dependent and volatile metabolites-dependent increases in EV production, we utilized nematodes with genetic ablations of sensory neurons known to mediate pathogen recognition38–40 and in exopher regulation22. Systematic analysis using animals carrying established genetic ablations of specific sensory neurons41–45, revealed that removal of ADL, ASK, or AWC neurons completely abolished exopher upregulation induced by both volatile metabolites and the non-volatile secretome (Fig. 5a-c). Conversely, the removal of AQR/PQR/URX, which we previously identified as regulators of exophergenesis22, had no effect in either assay, similar to ASJ ablation (Fig. 5a-c). Interestingly, we observed discrepancies among ASI, ASH, and AWB neurons. While ASI, ASH, and AWB neurons were crucial for the non-volatile secretome-induced increase, they do not play a role in the volatile metabolites-dependent increase in EV production (Fig. 5a-c). Notably, ablation of ADL or ASK also reduced baseline exopher levels (Fig. 5a and c), consistent with our previous work showing that these neurons contribute to exophergenesis regulation at the basal level22. Finally, when comparing each ablation to wild type under non‑volatile secretome exposure, all sensory‑neuron mutants except ASI and AQR/PQR/URX showed a significantly attenuated exopher response, with ASK and ADL mutants exhibiting the largest reductions, whereas AQR/PQR/URX-ablated and ASI-ablated worms produced more exophers than wild type and the same number as wild type, respectively (Supplementary Fig. 4b). For volatile metabolites, AQR/PQR/URX and ASI ablations likewise enhanced exopher induction, AWB ablation had no measurable effect, and the response was reduced in all other neuron‑ablated strains (Supplementary Fig. 4a). Altogether, these findings show that multiple types of sensory neurons regulate exopher production in response to pathogen-produced compounds in a context-dependent manner, with ADL, ASK, and AWC neurons playing pivotal roles.

A hierarchical neural circuit regulates exopher production in response to pathogen secretomes
To map the downstream interneuron circuit, we took a dual approach. A literature search for a central integrator of the previously identified sensory neurons pointed to the RMG interneuron, a known “hub-and-spoke” network center46. Separately, a search of the C. elegans connectome for downstream partners highlighted the AIA and AIB interneurons47. Notably, AIA and AIB, along with the AIB-specific neuropeptide receptor NPR-9, have previously been implicated in regulating C. elegans immunity48,49, making them prime candidates for mediating this physiological response.

Our functional data confirmed the critical role of the RMG hub. Genetic ablation of RMG not only reduced basal exophergenesis but also completely abolished the induced response to both volatile and non-volatile pathogen cues (Fig. 6a–c, and Supplementary Fig. 5a and b), establishing it as an essential, central integrator.

Next, we examined the roles of the candidate processing interneurons. Ablation of AIA revealed a striking, context-dependent function. While AIA removal caused a modest, non‑significant reduction in basal exopher levels (Fig. 6d), AIA‑deficient worms still responded to volatile metabolites with a significant but attenuated increase in exopher production (Fig. 6e, and Supplementary Fig. 5a). In contrast, exposure to the non-volatile secretome failed to elicit any induction (Fig. 6f, and Supplementary Fig. 5b). These results indicate that AIA is essential for non‑volatile secretome-driven exophergenesis and plays a modulatory role in the volatile metabolites‑mediated response (Fig. 6k).

Genetic ablation of AIB did not affect basal exopher production, whereas loss of the inhibitory receptor NPR‑9, a condition that is known to activate AIB48, reduced basal exopher levels (Fig. 6g). Consistent with the results from the npr-9 mutant, optogenetic activation of AIB for 4 hours via ReaChR50 also significantly decreased exopher production (Fig. 6h). Upon exposing worms to P. aeruginosa secretomes, the removal of the AIB neurons or NPR-9 receptor significantly reduced the increased exophergenesis induced by pathogen volatile metabolites (Fig. 6i, Supplementary Fig. 5a) and non-volatile secretome (Fig. 6j, and Supplementary Fig. 5b), with a more pronounced effect for volatile metabolites exposure. These results suggest that the AIB interneurons and NPR-9 receptor are essential for mediating exopher production in response to pathogen signals (Fig. 6k).

In summary, our findings delineate a multi-layered circuit that processes pathogen threat information (Fig. 6k). Increased exopher production due to volatile metabolites sensing relies primarily on the ASK, ADL, and AWC sensory neurons, which signal through the AIB and RMG interneurons, with AIA interneurons acting as a modulator (Fig. 6l). In contrast, increased exopher production due to non‑volatile secretome sensing engages an expanded circuit that includes ASI, AWB, and ASH inputs, alongside ASK, ADL, and AWC, converging on the same AIB and RMG core, but with stronger AIA involvement (Fig. 6m).

Identification and functional characterization of GPCRs mediating pathogen-induced exophergenesis
G-protein-coupled receptors (GPCRs) are essential mediators that enable cells to interact with their environment by transmitting signals. In both vertebrates and invertebrates, GPCRs play a key role in coordinating immune responses51,52. Because exopher induction is triggered by chemical cues from pathogenic bacteria, we hypothesised that specific GPCRs act as sensors linking pathogen-derived signals to neuronal circuits controlling exophergenesis. To identify such receptors, we adopted a transcriptomic approach combining published datasets and new RNA-sequencing experiments.

First, we analysed published transcriptomics data from worms exposed to P. aeruginosa compared to worms grown on E. coli OP5053. Among the most significantly upregulated GPCRs were sri-36 and sri-39, with fold changes of 480 and 79.5, respectively. According to a study by Vidal et al.54., these GPCRs are expressed in ASK and ASI cells, which we have shown to play an important role in exopher upregulation (Fig. 5a-b). Additionally, our prior RNA sequencing, which identified the GPCR str-173 as a regulator of socially-mediated exopher production, also ranked sri-36 and sri-39 among the top candidates associated with exopher regulation22, further justifying their selection for validation.

To broaden this search and identify receptors associated with natural variation in exopher output, we conducted RNA sequencing on age-synchronized wild-type worms that exhibited either high (more than 20) or low (fewer than 2) number of exophers on adulthood day 2. A similar strategy, utilizing gene expression heterogeneity within isogenic populations, was recently employed to study the processes that generate lifespan variation55. The results of this RNA sequencing show that worms producing a high number of exophers differ significantly at the transcriptomic level from worms producing low number of exophers (Fig. 7a). Specifically, 609 genes were upregulated and 665 genes were downregulated (padj<0.05; -1>log2 fold change>1) (Fig. 7b and Supplementary Data 2). GO enrichment analysis revealed upregulation of “cilium assembly” (Fig. 7d), consistent with the central role of ciliated neurons in exopher regulation22. Among the significantly altered genes were three GPCRs; str-173, srr-6, and sri-19, whose expression correlated with exopher number (Fig. 7c). As str-173 had been validated previously as a pheromone-responsive regulator22, srr-6 and sri-19 were selected for functional analysis alongside sri-36 and sri-39, yielding four prime receptor candidates for experimental validation.

To examine their functions, we generated CRISPR/Cas9 mutants for each locus (Supplementary Fig. 6). Because sri-36 and sri-39 are separated by only 1.9 kb, with one gene situated between them, they were deleted together to produce an sri-36/39 mutant. Under baseline conditions, exopher levels were similar to wild type in sri-19 and sri-36/39 mutants (Fig. 8a and e), while it was mildly upregulated in srr-6 mutant (Fig. 8i). Upon exposure to pathogen cues, a clear functional divergence emerged. All receptor mutants exhibited a statistically significant increase in exopher production following exposure to volatile metabolites (Fig. 8b, f, j). The responses of sri-36/39 and srr-6 mutants were comparable to wild type (Supplementary Fig. 7c, e), whereas the sri-19 mutants showed a significantly attenuated response (Supplementary Fig. 7a). In stark contrast, the response to the non-volatile secretome was completely suppressed in all tested mutants (sri-19, sri-36/39, and srr-6), indicating they are all essential for this pathway (Fig. 8c, g, k, Supplementary Fig. 7b, d, f). Underscoring its central role, the sri-19 mutant also failed to upregulate exopher production upon exposure to live P. aeruginosa bacteria (Supplementary Fig. 7g).

Expression analysis provided the crucial link between these molecular players and the previously identified circuits. The wrmScarlet CRISPR/Cas9-mediated transcriptional knock-in of the sri-19 gene revealed its expression in ADL and PHA neurons (Fig. 8d, and Supplementary Fig. 7h, i). Furthermore, transcriptional reporters using fluorescent proteins for the sri-36 and sri-39 genes indicated expression in anterior ciliated neurons (Fig. 8h), which, based on available literature54, correspond to ASI and ASK neurons. However, we must not note that we used a double deletion at the sri-36/39 locus, the observed phenotype in exopher production could be driven by loss of only one receptor, with the other making little or no contribution. Nonetheless, the expression pattern of all three receptors is consistent with our data, underscoring the critical role of ADL, ASK, and ASI neurons in pathogen-induced exopher production and establishing its molecular mechanism.

Finally, the expression of the srr-6 receptor in neurons of the retrovesicular ganglion (RVG), alimentary tract, and excretory system (Fig. 8l), as well as the expression of sri-36 and sri-39 in the alimentary tract (Fig. 8h), suggest that one or more of these tissues may also play a role in regulating exopher production in muscles. To test this, we drove srr-6 expression specifically in the intestine. This intestinal rescue not only restored the non-volatile secretome-dependent exopher response but also reduced basal exopher levels, a result consistent with array-mediated overexpression, demonstrating that SRR-6 functions in the intestine to regulate muscle exopher production (Supplementary Fig. 7j) and revealing a novel gut-muscle signalling axis.

Offspring of animals exposed to pathogen volatile metabolites show improved survival post-infection
We aimed to investigate the functional consequences of extracellular vesicles release when worms detect the pathogen in their environment. Prompted by a recent study showing that perception of Pseudomonas vranovensis volatiles confers intergenerational protection in C. elegans56, we examined both offspring and maternal outcomes following pre-exposure to P. aeruginosa cues. Specifically, we assessed progeny survival and developmental rate during P. aeruginosa infection following parental pre-exposure to volatile metabolites or non-volatile secretomes, and evaluated how this preconditioning impacted hermaphrodite mothers’ survival upon subsequent P. aeruginosa infection (Fig. 9a). For these assays, P0 worms were exposed to P. aeruginosa volatile or non-volatile secretomes for 48 hours beginning at the L4 stage. To assess progeny outcomes, F1 embryos were collected at the 3-fold stage, transferred to P. aeruginosa–seeded plates at 20°C, and scored after 48 hours for survival and developmental progression (scored as younger than L4, or L4 and older). For maternal survival, P0 adults (exposed to secretomes until day 2 of adulthood) were transferred to fresh P. aeruginosa plates and monitored every few hours until death. Pre-exposure of P0 adults to P. aeruginosa volatiles significantly increased F1 survival under infection (Fig. 9b) without altering their rate of development to L4/adulthood (Fig. 9c). However, this effect did not persist in the F2 generation, where no significant differences in survival or development were observed (Supplementary Fig. 8a and b).

P0 pre-exposure to non-volatile secretomes had no effect on either progeny survival or developmental timing (Fig. 9d and e). For P0 mothers, volatile preconditioning produced a slight, non-significant decrease in survival on P. aeruginosa (Fig. 9f), whereas non-volatile preconditioning had no measurable impact (Fig. 9g).

We next asked whether the SRI-19 receptor, essential for exopher induction by P. aeruginosa and its secretomes, also influences progeny outcomes. Following P0 pre-exposure to P. aeruginosa volatiles or secretomes, sri-19 mutants displayed no differences in F1 survival or developmental rate (Fig. 9h-k). This result indicates that the enhanced offspring resilience conferred by parental exposure to P. aeruginosa volatiles depends on the SRI-19-mediated pathway.

Elevated temperature of 25°C both enhances exopher production in C. elegans22 and increases P. aeruginosa virulence. Because wild worms encounter pathogens in a range of environmental temperatures, we assessed how F1 survival and development are affected at 25°C. As shown in Supplementary Fig. 9a–d, these high-temperature outcomes differ markedly from those at 20°C (Fig. 9b–e). Progeny of parents pre-exposed to P. aeruginosa volatiles developed faster (Supplementary Fig. 9b) but showed unchanged survival (Supplementary Fig. 9a), whereas progeny of parents exposed to P. aeruginosa non-volatile secretome suffered both reduced survival and delayed development compared to unexposed controls (Supplementary Fig. 9c and d). In P0 adults, pre-exposure to P. aeruginosa volatiles significantly decreased survival upon subsequent P. aeruginosa infection (Supplementary Fig. 9e), while pre-exposure to non-volatile secretome had no effect (Supplementary Fig. 9f). Notably, sri-19 mutants, accumulated fewer embryos in utero (Supplementary Fig. 9g), and are unable to upregulate exophers in response to P. aeruginosa, but survived significantly longer during infection (Supplementary Fig. 9h). Likewise, knockdown of the yolk receptor RME-2, which nearly abolishes exopher production18, and reduces embryo accumulation in utero (Supplementary Fig. 9i) also conferred enhanced resistance to P. aeruginosa (Supplementary Fig. 9j). Together, these data demonstrate that parental sensing of P. aeruginosa volatiles enhances offspring resilience at 20°C, while elevated environmental temperature abolishes this effect, underscoring its context-dependent nature. Finally, SRI-19’s role in this pathway directly links the machinery of exopher biogenesis to survival outcomes, highlighting how EV production and organismal fitness are mechanistically intertwined.

Methods
Worm Maintenance and Strains
C. elegans strains were maintained at 20°C (unless otherwise indicated) on nematode growth medium (NGM) plates seeded with Escherichia coli OP50 as a food source69. Only hermaphrodites were used in the experiments. A comprehensive list of all strains and chemicals used in the study is provided in Supplementary Data 3 and 4, respectively.

Pathogen procedures
Pathogen bacteria media plates preparation. Worms were exposed to either Pseudomonas aeruginosa PA14 or Serratia marcescens Db10 strains. Pathogen-seeded plates were prepared following standard protocols70,71. All the experiments with the pathogenic bacteria were conducted in Biosafety level 2 laboratory.

Pseudomonas aeruginosa PA14 “slow-killing” (SK) plates preparation. The PA14 strain was revived from frozen stock by streaking onto a 10-cm LB agar plate and incubating at 37°C for 12–18 hours. Plates were stored at 4°C and used within one week. A single PA14 colony was inoculated into 5 mL of LB broth and incubated overnight (maximum 16 hours) at 37°C with shaking at 250 rpm. Following incubation, 10 μL of the overnight PA14 culture was spotted onto the center of 35 mm “slow killing” plates (SK plates), which were incubated at 37°C for 24 hours, followed by 25°C for another 24 hours to maximize virulence.

Serratia marcescens Db10 plates preparation. For S. marcescens Db10, the strain was similarly streaked from frozen stock onto a 10-cm LB agar plate, incubated at 37°C for 12–18 hours, and stored at 4°C for up to one week. A single Db10 colony was inoculated into 5 mL of LB broth and cultured at 37°C with shaking for 8–10 hours. To prepare NGM infection plates, 25 μL of the S. marcescens culture was seeded onto 35 mm NGM plates, which were incubated at 37°C overnight.

Short-time infection assay. Worms were age-synchronized by isolating 3-fold stage embryos (hand-picked under a stereomicroscope). Upon reaching the first day of adulthood (AD1), they were transferred either to control plates seeded with E. coli OP50 or to plates seeded with the pathogens PA14 or Db10. Worms were exposed directly to the pathogens for 3 hours at 25°C, after which they were transferred back to OP50 seeded plates. Exopher levels were assessed the following day, on the second day of adulthood (AD2).

Pathogen non-volatile secretome assay. To collect non-volatile secretome, a single colony of PA14 was inoculated into 5 mL of LB media and cultured overnight for a maximum of 16 hours at 37°C. After incubation, bacterial cells were removed by passing the culture through a 0.22 μm filter (Sarstedt, Filtropur S, no. 83.1826.001), and the bacterial supernatant was collected. Age-synchronized L4 stage worms (n=30), grown on 60 mm NGM plates seeded with OP50, were treated with 50 μL of the filtered bacterial supernatant, while control worms received 50 μL of LB broth. Plates were sealed with parafilm, and exophers were scored 48 hours later, when the worms reached AD2.

Volatile metabolites chamber assay. 3-fold stage embryos were placed on 35-mm NGM plates seeded with E. coli OP50, with 10 embryos per plate. Once the embryos developed into L4 stage worms, a chamber with volatile metabolites was assembled by placing a 35 mm SK plate containing PA14 or a control 35 mm NGM plate with OP50 on the bottom. The plate with synchronized worms was positioned on top, and the two plates were sealed together with parafilm. Worms were incubated with volatile metabolites of the bacteria for 48 hours. Exophers were evaluated on the second day of adulthood.

Parental generation survival. The parental generation (P0) of C. elegans was synchronized by transferring 10 3-fold stage embryos onto NGM plates seeded with Escherichia coli OP50. When the worms reached the L4 larval stage, they were subjected to the “Volatile Metabolites Chamber Assay” or “Pathogen non-volatile secretome assay” as previously described. After 48 hours of exposure to the volatile or non-volatile secretomes, exopher production was quantified in the P0 generation at AD2. The P0 worms were then moved to SK plates seeded with PA14 and maintained at 20°C (Fig. 9f, g) or 25°C (Supplementary fig. 8e-h). The use of 5-fluoro-2′-deoxyuridine (FUdR) was omitted from all plates. Survival of the P0 population was monitored at multiple time points using a touch-provoked movement assay. Worms that did not respond to touch were recorded as deceased, removed from the killing plates, and documented. Those that responded to touch were considered alive and were counted accordingly. Survival data were collected at least twice daily until the death of the entire population.

Offspring survival and development assay. Once the parental generation (P0) of worms reached the L4 larval stage, they were subjected to the “Volatile Metabolites Chamber Assay” or “Pathogen non-volatile secretome assay”. After 48 hours of secretome exposure, exopher production was quantified in the P0 generation on the second day of adulthood (AD2).

To assess intergenerational effects, 3-fold stage embryos of the F1 generation, derived from P0 worms were collected and transferred to 35 mm SK plates seeded with PA14 bacteria (10–15 embryos per plate). The plates were incubated at 20°C (Fig. 9b-e, h-k) or 25°C (Supplementary fig. 8a-d). Offspring survival and development were assessed after 48 h by scoring the total number of worms and determining their developmental stages. Developmentally advanced or delayed were excluded from the experiment.

Embryo accumulation assay. First, AD1 age-synchronized worms were placed on either a lawn of pathogenic bacteria (PA14 and Db10) or a control lawn of OP50 for 3 hours. After exposure, worms were transferred to OP50 plates and cultured until they reached the AD2 stage. In the next step, hermaphrodites were treated with 1.8% hypochlorite solution. Once the worms dissolved, the embryos retained in the uterus were counted.

RNA Interference Assay. RNA interference (RNAi) in C. elegans was performed using the standard RNAi feeding method72. Briefly, RNAi plates were prepared by supplementing NGM with 12.5 μg/mL tetracycline, 100 μg/mL ampicillin, and 1 mM IPTG. These plates were seeded with E. coli HT115 bacteria expressing double-stranded RNA (dsRNA) targeting the gene of interest. Control worms were fed E. coli HT115 containing the empty vector L4440.

Age-synchronized 3-fold stage embryos were transferred onto the freshly prepared RNAi plates and cultured until day 2 of adulthood, at which point exophers were quantified. The developmental stage of the worms was confirmed at the L4 stage, and any individuals that were developmentally advanced or delayed were excluded from the experiment.

Metabolomic analysis. All solvents were prepared prior to analysis: extraction solvent was prepared by mixing 1 mL of LC-MS grade methanol, 4.5 mL of LC-MS grade acetonitrile and 4.5 mL of LC-MS grade isopropanol; 90% acetonitrile was prepared by mixing 9 mL of LC-MS grade acetonitrile with 1 mL of MQ grade water; mobile phase A (MPA) was prepared by adding 1 mL of formic acid and filling it to 1 L with MQ grade water; mobile phase B (MPB) was prepared by adding 1 mL of formic acid and filling it to 1 L with LC-MS grade acetonitrile. Metabolite extraction was achieved by transferring 50 μL of the sample to an Eppendorf LoBind tube and adding 250 μL of ice-cold extraction solution of methanol:acetonitrile:isopropanol (2:9:9, v/v/v). Samples were shaken for 10 min at 1500 RPM in RT and subsequently centrifuged for 10 min at 14000 RPM at 4°C. Supernatants were transferred to new polypropylene sample tubes and evaporated to dryness under nitrogen stream at 50°C using Caliper TurboVap LV evaporator. Dry residue was reconstituted by addition of 100 μL of 90% acetonitrile, vortexed and centrifuged.

LC-MS analysis was performed using ACQUITY UPLC system (Waters) coupled with Q-Exactive Orbitrap high resolution mass spectrometer (Thermo Scientific). Chromatographic separation was achieved using ACQUITY UPLC BEH HILIC column (130 Å, 1.7 μm, 2.1 mm × 100 mm). MPA was 0.1% formic acid in MQ grade water and MPB was 0.1% formic acid in LC-MS grade acetonitrile. The initial gradient conditions were 100% B with mobile phase flow rate at 0.4 mL/min and was held for 1 min. The mobile phase composition changed to 90% B over next 6 min, then dropped to 50% B at 9 min, and to 10% B at 10 min to be kept for next 4 min. Column was re-equilibrated by changing the gradient back to initial conditions. The total method run time was 20 min. The mass spectrometer operated in separate positive (ESI+) and negative (ESI-) electrospray ionization. The tune parameters were as given: sheath gas flow rate 55.0 [a.u.], auxiliary gas flow rate 15.0 [a.u.], sweep gas flow rate 4.0 [a.u.], spray voltage in ESI+ was 4.0 and in ESI- was 3.5, S-lens RF 30.0 [a.u.]. Capillary temperature was set to 320°C and auxiliary gas temperature to 350°C. Data acquisition was proceeded in Data Dependent Acquisition (DDA) mode, MS1 resolution set to 70,000, MS1 AGC Target 1.0 × 10^6, MS1 Maximum Injection Time 90 ms, scan range 120 to 1600 m/z, and MS2 resolution was set to 35,000, MS2 AGC Target to 1.0 × 10^5, MS2 Maximum Injection Time 100 ms, Top N was 8, isolation window 2.0 m/z and normalized stepped collision energy of 20, 30 and 40 was used to collect fragmentation spectra.

Raw data were uploaded to Compound Discoverer 3.3.3 (Thermo Scientific). An in-house protocol for metabolomic search and identification was employed. The workflow tree consisted of: Input Files → Select Spectra (any polarity, precursor mass 100–1500 Da, MS(n-1) precursor selection) → Align Retention Times (adaptive curve alignment model, max mass tolerance 10 ppm, max shift time 2.0 min) → Detect Compounds (mass tolerance 15 ppm, signal/noise > 5, max peak width 0.3 min, base ions [M+H]+ and [M-H]-) → Merge Features (mass tolerance 15 ppm and RT tolerance 0.5 min) → Group Compounds (mass tolerance 10 ppm, RT tolerance 0.2 min, all peaks used for area integration, preferred ions [M+H]+ and [M-H]-) → Fill Gaps (mass tolerance 5 ppm, signal/noise > 3) → Normalize Areas (Median Absolute Deviation model) → Mark Background (max sample/blank = 5). Predict Composition node was set to mass tolerance of 5 ppm, isotope intensity tolerance of 30%, and minimum pattern coverage of 90%. Metabolomika Pathways, mzVault, mzCloud and ChemSpider databases were selected for analytes identification and assignment. Identifications were analyzed using mzLogic node with minimum match threshold of 30 and high resolution fragment mass tolerance 15 ppm.

XCalibur 3.0.63 (Thermo Scientific) software was used to design LC-MS workflow and acquire sample batch, as well to analyze raw mass spectra using built-in Qual Browser. OpenMS 3.4.0 software was used to visualize the raw fragmentation spectra. ACD/ChemSketch 2024.2.3 (ACDLabs) was employed to determine the fragmentation pattern of isoleucyl-prolyl-proline tripeptide.

Ile-Pro-Pro tripeptide assay. Worms were age synchronized from 3-fold stage embryos and cultured on 60 mm NGM plates seeded with E. coli OP50 bacteria. A total of 50 μL Ile-Pro-Pro solution (containing 50 μM or 100 μM) was applied to plates with worms on adulthood day 1. Plates were left open under the hood to dry for 30 minutes and incubated for further 24 hours at 20°C. BWM exophers were scored on day 2 of adulthood, after 24h exposure to tripeptide. Synthetic, concentrated stock solution of Ile-Pro-Pro was stored in H2O at -80°C. The stock was diluted to working solutions with M9 buffer.

Transcriptome analysis. C. elegans RNA extractions, library preparations, and sequencing were performed by Azenta US, Inc (South Plainfield, NJ, USA) as follows:

RNA extraction. Total RNA was extracted using Qiagen RNeasy Plus mini kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions.

Library preparation with polyA selection and Illumina sequencing. RNA samples were quantified using the Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA), and their integrity was assessed with the Agilent TapeStation 4200 (Agilent Technologies, Palo Alto, CA, USA). RNA sequencing libraries were constructed using the NEBNext Ultra II RNA Library Prep Kit for Illumina, following the manufacturer’s protocol (NEB, Ipswich, MA, USA). In brief, mRNA was enriched using Oligo(dT) beads and subsequently fragmented at 94°C for 15 minutes. First and second-strand cDNA synthesis was performed, followed by end repair and adenylation of the cDNA fragments at their 3’ ends. Universal adapters were then ligated to the cDNA fragments, and libraries were enriched through a limited-cycle PCR with the addition of indexing sequences. The resulting sequencing libraries were validated using the Agilent TapeStation and quantified with both the Qubit 2.0 Fluorometer (Invitrogen, Carlsbad, CA, USA) and quantitative PCR (KAPA Biosystems, Wilmington, MA, USA). The libraries were multiplexed and loaded onto the Illumina NovaSeq 6000 platform according to the manufacturer’s instructions. Sequencing was performed with a 2×150 paired-end (PE) configuration using v1.5 reagents. Image analysis and base calling were carried out using the NovaSeq Control Software v1.7. The raw sequence data (.bcl files) generated were converted into fastq files and de-multiplexed using the Illumina bcl2fastq software (version 2.20), allowing for one mismatch in index sequence identification.

Sequencing data analysis. Following quality assessment of the raw sequencing data, reads were trimmed to remove potential adapter sequences and low-quality nucleotides using Trimmomatic v0.36. The cleaned reads were then aligned to the Caenorhabditis elegans reference genome from ENSEMBL using the STAR aligner v2.5.2b. STAR is a splice-aware aligner that identifies splice junctions and integrates them into the alignment process to enhance the accuracy of read mapping. This step resulted in the generation of BAM files. Unique gene hit counts were calculated using the featureCounts function from the Subread package v1.5.2, considering only reads uniquely aligned to exon regions.

The gene hit counts were subsequently used for downstream differential expression analysis. DESeq2 was employed to compare gene expression levels between different sample groups. The Wald test was used to calculate p-values and log2 fold changes. Genes with an adjusted p value < 0.05 and an absolute log2 fold change > 1 were considered differentially expressed in each comparison.

Scoring of Muscle Exophers and Fluorescence Microscopy. Exopher quantification was performed as described in Turek et al.18 and Banasiak et al.24 (Bio-Protocol, detailed, step-by-step guide). In brief, exophers were scored using a Zeiss AxioZoom.V16 stereomicroscope equipped with filter sets 63 HE and 38 HE. Worms were age-synchronized by isolating 3-fold stage embryos (hand-picked under a stereomicroscope) and maintained until day 2 of adulthood. On the second day of adulthood, worms were observed on NGM plates, and the number of exophers per freely moving worm was counted.

Figure 1f-i experiments were performed using different experimental setup. Exophers were scored using a Leica DMRBE microscope equipped with a 20× objective and RFP filter. Worms were age-synchronized by isolating 3-fold stage embryos or L4 stage larvae and maintained until day 2 of adulthood. During the infection period with PA14 or Db10 (or OP50 as a control), worms were briefly incubated at 25°C for three hours. On day 2 of adulthood, animals were immobilized on 2% agarose pads with a 50 mM NaCl drop (10–20 μl), and the number of exophers per worm was scored.

Scoring of neuronal exophers. Neuronal exophers were scored using a Leica STELLARIS 8 FALCON confocal system with a 40× oil immersion objective. For imaging, worms were immobilized on 5% agarose pads (dissolved in M9), 10 μM tetramisole as an anesthetic.

Optogenetics assays. For optogenetic activation, both control and experimental 35 mm NGM plates seeded with E. coli OP50 bacteria were covered with 0.2 μM all-trans retinal (ATR) and left to dry at 20°C and darkness for 16 hours. Ten to twelve age-synchronized worms were picked per plate from optogenetic strains expressing ReaChR in AIB at adulthood day 2. After a 3-hour incubation at 20°C and in darkness, BWM exophers were scored. Next, experimental plates were placed under the source of white light (light intensity measured at 594 nm = 0.02 mW/mm^2) for 4 hours. Control plates were shielded from light. The muscle exophers were counted immediately after illumination. Control and treated groups were randomized before the start of the experiment.

Fluorescence Microscopy. Representative fluorescence images in Fig. 1a, Fig. 2b, and Fig. 2f were acquired using a Leica STELLARIS 8 FALCON confocal microscope equipped with an HC PL APO CS2 40×/1.30 oil-immersion objective. GFP and RFP fluorescence were excited using 494 nm and 575 nm laser lines, respectively. Images in Fig. 1a were captured in LIGHTNING deconvolution mode to enhance spatial resolution. The left and middle panels show single optical sections, while the right panels present a three-dimensional reconstruction of the corresponding z-stack generated in LAS X 3D Viewer (Leica Microsystems). Images in Fig. 2b and Fig. 2f were acquired in standard confocal mode and represent maximum-intensity projections of z-stacks.

Representative fluorescence images in Fig. 7d, Fig. 7h, Fig. 7l, and Supplementary Fig. 7i were obtained using a Zeiss LSM 800 laser-scanning confocal microscope equipped with an EC Plan-Neofluar 40×/1.30 Oil DIC M27 objective. GFP and RFP were excited with 488 nm and 561 nm laser lines, respectively, and all panels represent maximum-intensity projections of confocal z-stacks.

For imaging, worms were mounted on 5% agarose pads and immobilized using either 10 μl of 0.05 μm polystyrene microspheres (PolySciences) or 25 μM tetramisole as an anesthetic.

Generation of sri-19, sri-36/39, and srr-6 mutant strains. CRISPR/Cas9 genome editing was employed to generate the sri-19 mutants (sri-19(wwa15) and sri-19(wwa16)) following previously established protocols73. The crRNA sequence used to target the sri-19 locus was ATAATTGGTGGATATACAAATGG. Mutations were mapped to the first exon, resulting in frameshifts that likely produce molecular null alleles.

To create srr-6 mutants, a previously described STOP-IN strategy74 was used, which introduces an early stop codon within the first exon. The crRNA sequence used to target the srr-6 locus was ACTCCAAGTCCTGAAGTCGT, and the STOP-IN cassette sequence was GGGAAGTTTGTCCAGAGCAGAGGTGACTAAGTGATAA, flanked by AATCTTTTTCAACAATGATTACTCCAAGTCCTGAAGTCGT (left) and GGGTGACGAGGTTTCGTGTCCATCTATTATTGAAATACCT (right).

For the deletion of both the sri-36 and sri-39 genes, the entire 5968 bp region encompassing both genes (including the intercalated gene F33H12.7) was removed and replaced with a STOP-IN cassette (GGGAAGTTTGTCCAGAGCAGAGGTGACTAAGTGATAA). The flanking sequences were TGGTTACTTTTTATTTTTATTTTTC (left) and AATCCTAATCTAATATGAATCAATT (right). The crRNA sequences used for this deletion were ACAATGCTAGTTGTAGGTAC and ATTCATATTAGATTAGGATT.

All mutant strains were backcrossed twice with N2 wild-type worms to remove background mutations and verified using Sanger sequencing.

Generation of srr-6 transgenic rescue strains
Plasmids cloning. Rescue construct was generated by simultaneously inserting two fragments, promoter and gene of interest, into the linearized pMT27 vector using the SLiCE method (Seamless Ligation Cloning Extract). The pMT27 plasmid contains the unc-54-3’ UTR and an unc-119(+) rescuing sequence. Restriction sites used for plasmid linearization were HpaI and PciI). Promoter region was amplified by PCR from plasmid templates. For the gene insert, cDNA from C. elegans was used as a template.

The SLiCE reaction (10 μl total volume) consisted of 100 ng of linearized vector and promoter/gene inserts in a molar ratio approximately equimolar to the vector, ensuring ~30 bp overlapping sequences between vector and inserts. The reaction mixture also contained NEBuffer 2.1 (NEB) and 0.5 μl of T4 DNA polymerase (NEB). The mixture was incubated at room temperature for 2 minutes, then placed on ice to stop the reaction, followed by bacterial transformation using the MH1 cloning strain. Plasmid sequences were verified for correctness using Nanopore sequencing.

Transgenic lines preparation. Transgenic strain was generated by germline transformation by injecting rescuing construct for srr-6 gene (100 ng/μl of eft-3p::srr-6::unc-54-3’ UTR and 10 ng/μl of pGLOW77(-myo-2p::mNeonGreen) from Addgene as co-injection marker) to srr-6(wwa49) mutant.

Data Analysis and Visualization. Data analysis was performed using Microsoft Excel and GraphPad Prism 9. Graphical representations of the results were generated in GraphPad Prism 9.

Statistical Analysis. No prior statistical methods were applied to determine sample sizes. Worms were randomly allocated to experimental groups, and all experiments were conducted in a blinded fashion for the datasets presented in Fig. 2d, i; Fig. 3a, b; Fig. 4a, d; Fig. 5a; Fig. 6a–j; Fig. 8a–k; Fig. 9b–k; Supplementary Fig. 2a, d; Supplementary Fig. 3a, b; Supplementary Fig. 4a, b; Supplementary Fig. 5a, b; Supplementary Fig. 7a–g, j; Supplementary Fig. 8a–h. Because the data were not normally distributed, we employed nonparametric statistical tests. For pairwise comparisons, the two-tailed Mann–Whitney tests were used, while Kruskal-Wallis tests followed by Dunn’s multiple comparison test were applied for multi-group comparisons. A p value of <0.05 was considered statistically significant.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript by Kołodziejska et al., the authors found that both the volatile and non-volatile pathogen metabolites stimulate exophers generation in C. elegans. They dissected the chemosensation of volatile and non-volatile pathogen metabolites, including the chemosensory neurons as well as the potential GPCRs involved, and proposed the sensory signals are integrated by the AIB interneuron via NPR-9. Finally, they proposed the significance of such regulation in enhancing offspring survival against pathogen in the basis of compromising maternal survival. This work addresses an important mechanism on how species fight against pathogen infection in the aspect of population level, and unravelled the potential mechanism of metabolites perception. Besides, the manuscript is clearly written with a clear logical flow. However, there is still critical evidence lacking, that should be completed before publication:\n1. Whether the regulation of exopher genesis in muscle is similar as in other tissue, such as neurons? How do the metabolites sensed by the chemosensory neurons and integrated by AIB neurons pass to muscle cells? What molecular mechanisms mediate this intercellular communication? Are there additive effects of volatile and non-volatile metabolites on exopher generation?\n2. Why are multiple chemosensory neurons required for both volatile and non-volatile metabolites? For example, ASK, ADL, and AWC – do they use the same sets of GPCRs to sense both volatile and non-volatile metabolites?\n3. For the neuron-specific function experiments, the authors should perform rescue experiments to confirm. For example, rescue SRI-19 in ADL neurons.\n4. More evidence is required to confirm that AIB interneurons integrate both volatile and non-volatile signals via NPR-9. For instance, the authors could rescue NPR-9 in AIB neurons. Additionally, does activation of AIB neurons phenocopy the effect of volatile and non-volatile metabolites on exopher generation as well as offspring survival on pathogens?\nMinor:\n1. Why do the two sri-19 alleles present different behavior upon PA14-induced exopher generation?\n2. Line 264, the citation should be Fig. 8d instead of Fig. 8c.\n3. The PA14-induced exopher generation is even increased in the akt-1 mutants. The authors should at least discuss the potential reason.\n4. The format of citation 44 should be corrected.", "reviewer_2": "Review report for manuscript “Pathogen threat proximity shapes host extracellular vesicle production in pre-infection\nresponse”\n< Summary >\nKołodziejska et al. investigated how environmental signals from pathogens regulate the production of muscle-derived\nexophers in C. elegans hermaphrodite. The authors put forth a compelling set of findings on mechanisms of exophergenesis\nregulation in response to direct or indirect pathogen exposure:\n- Dependency of exophergenesis on four immune response pathways (p38 MAPK, Insulin signaling, TFP-beta, IPR) by\nanalyzing exopher production of the mutants\n- Distinct effect of exposure to pathogen, pathogen supernatant or pathogen volatile to exophergenesis\n- Identification of neuronal cells and molecules required for regulation of exophergenesis from muscles\n- Effect of changed exophergenesis level upon survival under pathogen infection state\nHowever, multiple conclusions throughout manuscript appear to extend beyond the experimental evidence. The details are\naddressed in comments.\nThe research report establishes, for the first time, that pathogen exposure can upregulate exophergenesis and release from\nmuscle cells. Given that this is the inaugural report on pathogen-responsive muscle exophers, it is crucial to document their\ncharacteristics. Fluorescence imaging data and detailed descriptions are vital in this context. Although the methods for\nobserving muscle-derived exophers are well-established by previous research, providing image data and comprehensive\ndescriptions of the exophers is essential.\nThe authors extensively addressed the mechanisms regulating exophergenesis in response to volatile and non-volatile\npathogen substances. While the data provide evidence for the roles of specific molecules and cells in the production of\nmuscle-derived exophers, the connection between the findings is not fully established. Additionally, the authors explore the\nintriguing phenomenon of muscle-derived exophers influencing lifespan regulation under pathogen-infected conditions.\nHowever, the study currently lacks key experiments needed to address several pivotal questions.\nTo meet the standards of Nature Communications and ensure the claims are fully supported by the data,\nsignificant additional experiments would be required. These experiments should validate the key conclusions\nand provide a stronger link between the proposed mechanisms and the observed phenomena, thereby enhancing the impact and rigor of the study.\n< Major comments by sections >\n< Introduction >\n1. Text line 88 “Our research demonstrates that worms can differentiate the proximity of a pathogen threat based on the type\nof metabolites they detect.”\nThe results of this research show that animals can differentiate the pathogen threat via pathogen-derived supernatant or\nvolatiles. However, whether they differentiate the \"proximity\" of pathogen based on the information has not addressed in this\nresearch.\n< Figure 1 and associated text >\n2. The consistency of results between Figure 1d and Figure 1e-g\nIn Fig. 1d, the authors suggest that the deficiency of genes involved in the immune response pathway results in significant\nchanges in the amount of exopher production from muscles. However, the experimental results under the same conditions\n(i.e., OP50 condition) for daf-16, tir-1, and dbl-1 mutants shown in Fig. 1e-g indicate apparently similar amounts of exopher\nproduction compared to wild-type animals. The authors should address the clear inconsistencies observed in the results.\nClarifying whether these differences arise from the experimental design or other confounding factors is essential for\nsupporting authors' conclusions of increased exopher production in the mutants upon pathogen exposure.\n3. Figure 1i and text line 127 “This indicates that the P. aeruginosa-dependent increase in exopher production operates\nindependently of the previously described embryo-maternal signalling, suggesting the involvement of a novel regulatory\npathway.\"\nIt is difficult to assert that the exopher production in response to PA14 is independent of embryo-maternal signaling only\nbased on the observation that the increase of exopher production was not accompanied by the increase of egg retention. To\nsubstantiate the claim, it is crucial that experiments be conducted to determine whether depleting embryos affects exopher\nproduction. Such studies are necessary to definitively conclude the independence of these processes.\n< Figure 2 and associated text >\n4. Figure 1i demonstrated that Pseudomonas aeruginosa does not lead to an increase in embryo accumulation in utero,\ncontrasting sharply with the effects of pathogen volatiles as illustrated in Figure 2c. These findings raise the possibility that\nnon-volatile pathogenic stimuli may suppress the embryo accumulation typically induced by exposure to pathogen volatiles.\nThe authors are encouraged to provide a detailed explanation for these divergent outcomes.\n5. In this manuscript, the terms 'bacterial supernatant' and 'bacterial non-volatile metabolites' appear to be used\ninterchangeably. However, as bacterial supernatant also contains a variety of substances including extracellular vesicles,\nwhich are not metabolites. Thus, it is recommended for the authors to define the range of the terms or discuss the limitation\nof the experiments. A similar level of explanation is also preferred for the bacterial volatiles used in this research.\n< Figure 3 and associated text >\n6. Figure 3a, c and text line 152 “Our results indicate that none of the tested pathways—including insulin, TGFβ, p38 MAPK,\nand IPR—significantly contribute to the volatile metabolite-dependent increase in EV production (Fig. 3a and c).”.\nIt might seem as though the authors are completely excluding the possibility that the pathways contribute to the pathogen\nvolatile-dependent increase in EV production. Considering potential for other scenarios, such as redundant contributions\nfrom these pathways, a more nuanced tone that leaves some room would be more appropriate.\n7. Figure 3b and c. The requirement of several immune response pathways for this EV production raises interesting\nquestions. Are these pathways working together to regulate exophergenesis? Discussing the interrelationships among these\npathways within the mechanism regulating exophergenesis could yield valuable insights.\n8. Text line 161 “… bypassing these pathways entirely for airborne signals.”\nSimilar with Major comment 8, excluding all the possibilities entirely is too definitive.\n< Figure 4 and associated text >\n9. The authors have not detailed the information for genetic ablation of each neuron in Methods section. Although the\ninformation is included in Supplementary Table 2 “Caenorhabditis elegans strains”, a brief description of the type of ablation\nwithin Methods and/or Results with reference to Table 2 would greatly enhance reader accessibility.\n10. Figures 4a-c demonstrate that the ablation of ADL or ASK neurons not only abolishes the upregulation of exopher\nproduction in response to pathogen volatiles or supernatant, but also the ablation itself considerably reduces exopher\nproduction already. The authors are not addressing this aspect.\n11. Figure 4a-c identify neurons required for upregulation of exopher production via stimulation from pathogen volatile or\nsupernatant. The results are indicating that lack of ADL or ASK neurons abolishes the upregulation. However, the data also\nreveal that ablation of each neuron itself results in a considerable reduction in exopher production, implying that the exopher\nproduction is constantly downregulated already by the neuronal ablation. Additionally, ASK-ablated strains show prolonged\nsurvival irrespective of pathogen volatile exposure experience, as depicted in Figure 8b. These findings suggest an\nunderlying complexity in the role of these neurons towards exophergenesis regulation that likely precedes their involvement\nin pathogen response. Given these complexities, it would be beneficial for the authors to further explore and discuss the\nimplications of neuronal ablation on general physiological functions. Clarifying these intricate relationships will enhance the\nmanuscript's depth and help substantiate the authors' conclusions.\n12. In Figure 4, the authors broadly investigated the contribution of multiple sensory neurons to the regulation of exopher\nproduction from muscles. It is noteworthy that these neurons are part of the \"Hub-and-Spoke\" system, with RMG functioning\nas the central hub (Ref. 35 and Macosko EZ et al., 2009). This raises the possibility that RMG may play a central role in\nregulating exophergenesis, potentially through its interactions with the sensory neurons studied in this research.\nInvestigating exopher production in neuron-ablated animals including RMG will enhance the understanding of circuit\nmechanisms underlying the nervous system's regulation of exophergenesis from muscles to substantiate novelty of this\nstudy.\n< Figure 7 and associated text >\n13. The arrangement of panels in Figure 7 is somewhat challenging to interpret. It may be more effective to reorganize the\nfigure by grouping panels according to their respective conditions. Additionally, while Figures 7, 3, and 4 share a similar\nexperimental design, Figure 7 includes statistical comparisons under basal conditions, which are not addressed in Figures 3\nand 4. Since the basal phenotypes of the mutant animals used could significantly impact the interpretation of their pathogen\nsubstance-responsive phenotypes, providing information on basal phenotypes is strongly recommended.\n14. Text line 230 “Notably, the basal level of exophergenesis in GPCR mutant worms under standard conditions remained\nunchanged (Fig. 7a, e, i). These findings collectively indicate that these receptors are critical for pathogen-induced exopher\nproduction, but not under non-stressed conditions.”.\nIt is stated that the basal level of exophergenesis in GPCR mutant animals remains stable under standard conditions;\nhowever, the results from sri-36/39 (wwa57), ssr-6 (wwa48), and ssr-6 (wwa49) show significant variations.\nThe authors need to reconcile these observations with their initial claims. Furthermore, as the mutants itself, without pathogen stimuli,\nshowed significant change of exophergenesis, it is misleading to claim “that these receptors are critical for pathogen-\ninduced exopher production, but not under non-stressed conditions.”. The authors must clearly delineate the observed\nphenotypes and articulate their contributions in light of the results obtained.\n< Figure 8 and associated text >\n15. The manuscript currently lacks a detailed description of the methods used for the parental survival assay. This\ninformation should be added to methods and described briefly in figure legends.\n16. Figure 8a presents an illustration that is challenging to interpret, despite a detailed legend that explains the experimental\nscheme. For instance, the notation 'exophers scored @AD2 F1 embryos collected' explains the procedure for Figures 8e\nand f. However, at first glance, it appears to pertain to the experiments shown in Figures 8b-d. To enhance clarity and ensure\nthat readers can easily follow the experimental design, the illustration requires improvement.\n17. Figure 8b. The effect of ASK neuron ablation on the prolonged survival of C. elegans under P. aeruginosa-infected\nconditions was previously reported by Venkatesh et al. (Life Science Alliance, 2023). The authors should reference this\nstudy to provide appropriate context and acknowledge prior findings.\n18. Figure 8b illustrates that exposure to pathogen volatiles, which increases exopher production from muscles, decreases\nthe survival rate under P. aeruginosa infection. The manuscript notes that prolonged survival due to ASK neuron ablation,\nwhich increases exopher production (Fig. 4a-c), supports the inverse correlation between exopher production and survival\nunder infection. These findings raise critical questions. Yet, several aspects need to be addressed to fully support the\nconclusions claimed by the authors. These include:\na. It is evident that ablation of the ASK neuron downregulates exophergenesis from muscles (Fig. 4a-c). This raise intriguing\nquestions, could the survival-extending effect observed with ASK ablation be attributed to the altered exophergenesis?\nWhat will be the roles of the ASK neuron in regulating both exophergenesis and survival? While the rme-2 RNAi experiment in\nFigure 4c supports the connection between exopher production and survival, the degree of survival extension observed with\nASK ablation appears to differ from that of rme-2 RNAi, implying a contradiction, which raises a concern that ASK's\npathogen susceptibility effect may be largely through pathways other than exophers. Addressing this crucial question will\nrequire additional experiments. For example, testing rme-2 RNAi in ASK-ablated animals or testing pre-exposure of\npathogen under rme-2 RNAi condition could provide valuable insights for understanding the complex biology.\nb. Previous research by Alcedo and Kenyon (Neuron, 2004) suggested that ASK has a longevity-promoting effect based on\ncombinational cell ablation experiments conducted under pathogen-free conditions. Interestingly, under pathogen-present\nconditions, ASK exhibits longevity-reducing effects. Given these contrasting observations, it would be valuable for the\nauthors to explore and discuss how ASK and ASK-dependently regulated exophers contribute to longevity mechanisms in\nthese opposing ways, depending on the presence or absence of pathogens.\n19. Figure 8c indicates that the knock-down of the rme-2 gene, known to decrease exopher production, also extends animal\nsurvival under infection, supporting the notion that reduced exopher production might enhance survival. Intriguingly,\nprevious research has shown that the exophergenesis event from touch neuron extends lifespan (text line 332 and Ref. 16),\nhighlighting a potential protective role of exophers in non-pathogenic contexts. This raises a crucial question, will enhancing\nexophergenesis from muscles through factors other than pathogen exposure, such as the knock-down of vit-1 or emb-27\ngenes, impact the survival of the animals under the condition tested in Figure 8c? This experiment can significantly\nstrengthen understanding for the roles of muscle-derived exophers in survival under pathogenic conditions.\n20. Figure 8c-d. The manuscript lacks clarity on whether the animals are exposed to pathogen volatiles prior to the survival\nassay. This critical information is not described in the legends, nor is it detailed in the Methods section. The information\nshould be addressed in Methods and depicted briefly in legends.\n21. Figure 8d and text line \"Additionally, sri-19 mutants, which do not show increased exopher production upon contact with\nP. aeruginosa non-volatile metabolites, survived significantly longer during infection (Fig. 8c) which demonstrates that on\nmechanistic level survival is interconnected with the regulatory elements for EV production.\".\nThe authors examined exopher production in sri-19 mutants in response to pathogen supernatant or volatile as shown in\nFigure 7b and c. Assuming that the protocol in Figure 8d adheres to that outlined in Figure 8a, the primary factor influencing\nthe survival of the mutant animals under pathogen infection would be the altered level of EV production induced by prior\nexposure to pathogen volatiles. However, Figure 7b indicates that EV production can be significantly upregulated even in\nthe absence of the sri-19 gene. These results raise a few questions:\na. Does pathogen infection significantly enhance EV production in sri-19 mutants?\nb. Which will dominantly impact on the survival of sri-19 mutants, pathogen supernatant or pathogen volatile?\nAnswering these two questions could provide a fundamental basis to demonstrate that survival is mechanistically\ninterconnected with the regulatory elements of EV production.\n22. In the study, survival assays utilized different initiation stages for P0 and F1 generation animals. P0 animals are exposed\nto P. aeruginosa starting from the day 2 adult stage, whereas F1 animals begin exposure at the L4 stage. It is crucial for the\nauthors to justify the choice of different stages for these experiments (why not adult day 2 for L1 animals) or clarify whether\nthe pathogen's effects on the lifespan of C. elegans are consistent across these developmental stages.\n23. Similar to Figure 8 discussed above, Fig. 8e and f lack sufficient labels to depict different conditions. Figure legend lacks\ninformation and it should describe what are shown in different subpanels. Additionally, an explanation of the error bars for\nFig. 8e and f should be provided to ensure clarity.\n24. The authors have sorted the P0 population into two categories based on criteria outlined on text line 280. However, the\nrationale for selecting these specific criteria is not provided. Detailed explanations are necessary for:\na. Why the numbers of exophers (7 and 10) were chosen as criteria for categorizing the biological replicates into high/low\nexopher groups. Although Supplementary Figure 2 and the associated text provide some basis for choosing these criteria, the\nprocess for selecting these specific numbers is not described. Furthermore, the authors should explain why the criterion\nchanged from the median values 6 and 10 in Fig. S2 to 7 and 10 in Fig. 8e and f. This is a critical problem that could be a\npotential violation of neutrality in the statistical tests.\nb. How the populations were handled for breeding and observation of exophers? Providing experimental details is crucial\nbecause this is a set of experiments on which authors' major claim \"volatile-induced exopher production enhances offspring\nsurvival against pathogen\" is based.\nc. We assume that Fig 8e shows the results of high-exopher group and Fig 8f show the low-exopher group. Then what are\nshown on the left end panels of Fig. 8e and f? Which threshold was used for which test? Why are there data that are both\nlower and higher than the thresholds?\n25. The left panel of Figures 8e and f represents exopher production across all examined individuals from multiple replicated\ngroups. However, to clearly demonstrate that each P0 group used to generate categorized F1 groups meets the established\ncriteria, it is essential to post the specific amounts of exopher production observed in each individual population.\nProviding this data will enhance transparency and allow for a more precise assessment of the experimental results.\n26. The authors propose that the increased exopher production due to exposure to pathogen volatile decreases the survival\nof P0 animals under pathogen exposure, while the survival of the F1 generation under the same conditions is enhanced at\nthe cost of the parent generation's survival. Figures 8e and 8f aim to demonstrate this hypothesis by comparing WT and\nWT+PA14 populations of P0 and F1 animals via survival assays.\nHowever, when analyzing the results within populations — for example, comparing WT animals above the criterion (Fig. 8e,\nthose producing more exophers) with WT animals below the criterion (Fig. 8f, those producing fewer exophers) — the results\nreveal conflicting phenotypes. Specifically, P0 animals above the criterion (Fig. 8e, middle panel) exhibit longer survival\nthan those below the criterion (Fig. 8f, middle panel), contradicting the notion that increased exophers reduce the survival of\nP0 animals under pathogen conditions proposed by the authors. Conversely, F1 animals derived from P0 animals above the\ncriterion (Fig. 8e, right panel) show shorter survival than those derived from below the criterion (Fig. 8f, right panel), which\nalso conflicts with the authors’ interpretation. The trend is consistent across WT and WT+PA14 populations in Figures 8e\nand 8f.\nThese findings not only conflict with the authors’ major novel claim in the research, but also contradict with the results\npresented in Figures 8b-d. The authors must address this significant discrepancy transparently and provide a detailed\nexplanation of their rationale for the data presentation and interpretation. Furthermore, a statistical analysis of the data within\nthe same population, specifically comparing subgroups divided by the criteria as mentioned earlier, is necessary.\nAdditionally, it is crucial to demonstrate that the survival-decreasing effects of pathogen volatile-responsive exophers in P0\nanimals under pathogen exposure are consistently observed within the experimental framework of offspring survival.\nClarifying these points is essential to resolve the discrepancies and ensure the validity of the conclusions.\n< Discussion >\n27. Text line 316 “This distinction implies that exophers may constitute distinct subtypes of EVs with unique molecular\ncompositions and functions.”\nThroughout the results, the authors have effectively demonstrated that the contribution of immune pathways to exopher\nproduction varies depending on pathogen-derived stimuli. However, the research has not explored whether the EVs\nproduced differ between various conditions or treatments. Instead, the survival assay results for ASK-ablated animals from\nFigure 8b, which ablation constitutively reduces EV production regardless of the type of pathogen-derived stimulus (Figure\n4a-c), could hint at a functional uniformity of the produced EVs. The potential heterogeneity might be suggested by\nassessing the distinctiveness of the generated exophers.\n28. Text line 331-337 “Previous studies have shown that increased exopher release can benefit the organism by removing\nprotein aggregates, extending lifespan, or promoting faster offspring development. However, when exopher release is\nelevated in response to pathogen exposure, we observe an opposite effect, leading to decreased survival upon infection.\nThis suggests that exophers, or possibly EV in general, may function under a hormetic response: while a moderate increase\nin EV production appears beneficial, an excessive increase may overwhelm the organism, negating any positive effects.”.\nThe authors focus their investigation on exophers, a specific subtype within the diverse family of extracellular vesicles.\nConsidering the well-established diversity of EVs in origin, characteristics, destination, and function, it is premature to extend\nthe findings of this study to all EVs. Furthermore, it is important to note that Reference 16 suggests distinct functions for\nneuron-derived exophers compared to the muscle-derived exophers examined here. This observation raises a fascinating\nquestion; why do neuron-derived exophers and muscle-derived exophers appear to have opposite effects on survival?\nThis intriguing contrast merits further discussion and exploration within the manuscript, rather than limiting the scope of\npotential implications.\n29. Text line 345 “In contrast, our study involved prolonged exposure to a mixture of volatile metabolites from pathogens,\nwhich may trigger different physiological responses.”.\nThe authors emphasize the potential importance of i) the duration of exposure and ii) the specificity of volatiles in mediating\nthe physiological responses of C. elegans to P. aeruginosa. Indeed, Ref. 31 demonstrates that short-term exposure (2 hours)\nto 1-undecene can improve survival under pathogen exposure, which contrasts with the effects indicated in the current\nresearch. However, to suggest the possible influence of the factors on the variation in physiological responses, the authors\nshould provide additional supporting evidence. For example, they could compare whether varying the duration of exposure\nto 1-undecene leads to different effects or not. Additionally, discussing which specific volatile compounds from pathogens\ncould underlie the observed physiological responses in this research would significantly enhance the depth and scope of\nthe discussion.\n< Minor comments >\n1. Text line 116 “However, when immune response mutants were exposed to pathogens, there here was a consistent\nincrease in exopher production across all tested mutants, as observed in wild-type worms (Fig. 1e-g).”\nIt could be read as all of the tested mutants are showing consistent increase in exopher production in response to pathogen\nexposure. However, in the following sentence, the authors mention that the cul-6 mutant is an exception. Therefore, the\nphrase 'across all tested mutants' may not accurately reflect the data and could be revised to account for the exception\nobserved in the cul-6 mutant.\n2. Text line 121 “Therefore, the pathogen-induced EV modulation does not rely on canonical immune response pathways.”\nGiven that the authors have not fully tested for redundancy in the immune response pathways, the claim that pathogen-\ninduced EV modulation 'does not rely on canonical immune response pathways' could be reconsidered. A more cautious\ninterpretation may be warranted until potential compensatory mechanisms are explored.\n3. Text line 124. egg retention\n4. Fig. 2a-c. The conditioning duration has changed from 3 hours for pathogen exposure (Fig. 1) to 48 hours for pathogen\nvolatile or supernatant exposure (Fig. 2; starting from L2 as described in Methods). The authors should at least comment the\nground for choosing 48 hours as pathogen volatile/supernatant conditioning to trigger exopher production. Is 3 hours too\nshort for the volatile/supernatant to exert effect?\n5. Figure 2a. The illustration presents an ambiguity; the stacked two plates in fourth row appear to be oriented with both top\nsides facing each other, which could potentially obstruct the passage of volatiles. If this is the case, the arrangement might\nimpede the intended experimental conditions and affect the reliability of the results.\n6. The authors should standardize the terminology used throughout the manuscript to maintain consistency. Specifically, the\nterms 'embryo accumulation' and 'egg(s) retention' are considered to refer to similar phenomena but are used\ninterchangeably. If the two terms are indicating different phenomena, describing the difference will help readers\nunderstanding better. Also, a unified terminology would enhance clarity and improve the manuscript's readability.\n7. Text line 145. EV in response or exopher in response\n8. Figure 2f and text line 148 “Notably, this increase in exopher production do not depend on increased egg retention in the\nworm's uterus (Fig. 2f).”\nDeciding that they “do not depend on” might be hasty conclusion. Although it is true that the increase in exopher production\noccurred without increased egg retention under exposure to pathogen supernatant, this does not exclude a possibility that\negg retention could affect the exopher production. Thus, “do not require” might be more accurate for this case.\n9. Figure 4a and text line 174 “While ASI, ASH, and AWB neurons are crucial for the supernatant-induced increase they do\nnot play a role in volatile metabolite dependent increase in EV production (Fig. 4a-c).”\nIn figure 4a, with ablation of ASH or AWB, while the amount of produced exophers is still significantly increased by pathogen\nexposure, the amount of change seems decreased compared to intact animals. To clarify this point, the magnitude of the\npathogen-induced increase in EV production could be statistically compared between wild-type and ablated animals. This\nanalysis could involve employing a two-way ANOVA approach, or its non-parametric variant, the Aligned Rank Transform\n(ART) ANOVA.\n10. In this research, ADL neuron is functionally ablated by hlh-4(tm604) III mutation. According to Masoudi et al., 2018, in\nPLoS Biology, this mutation disrupts the ‘identity features that define functional features of the ADL neuron’,\nwithout physically destroying the neuron. Since this approach differs from the methods used to ablate other neurons in the research,\nit is crucial to clearly delineate this discrepancy in the Materials and Methods section.\n11. Text line 191 “… receptor abolishes the …”.\nFigure 5c shows that while the increase in pathogen supernatant-dependent EV production in AIB(-) strains is not\nstatistically significant, there is a discernible increase in average levels. This implies that availability to regulate EV\nproduction is not completely eliminated. more accurate description of the observed effect might be 'significantly reduced,'\nwhich would more precisely reflect the experimental data.\n12. Test line 194 A period is missing after \"signals\".\n13. Text line 204 “Additionally, our prior RNA sequencing, which identified the GPCR str-173 as a regulator of socially\nmediated exopher production, also highlighted sri-36 and sri-39 as top candidates, further supporting their potential as\nstrong candidates for validation44.”.\nThe authors should elucidate how their previous RNA sequencing efforts have identified sri-36 and sri-39 as top candidates\nfor pathogen signal receptors. It is essential to clearly describe the criteria and analysis methods used to highlight these\ngenes, as well as any supporting data that distinguishes them from other candidates. Providing this detail will enhance the\nreader's understanding of the basis for these selections and strengthen the overall findings of the study.\n14. Text line 207 “To investigate the roles of sri-36 and sri-39 in exopher regulation, we employed CRISPR/Cas9 technology\nto generate a mutant with a deletion encompassing both receptor-encoding genes, as they are located only 1.9 kb apart, with\none gene situated between them (Supplementary Fig. 1).”\nThe propinquity of two gene, sri-36 and sri-39, upon genome accounts for the efficiency of simultaneous deletion to generate\ndouble (actually triple) mutant, but it cannot be the ground for not generating single mutants. Use of this mutant deleting\nmultiple genes leaves a possibility that the phenotypes are attributed to only one of the mutated genes, but the rests are not\ncontributing. The authors should discuss this limitation.\n15. Text line 221 (Fig. 6d) and text line 224 (Fig. 6c).\n16. Figure 7d and Text line 234 “The wrmScarlet CRISPR/Cas9-mediated transcriptional knock-in of the sri-19 gene\nrevealed its specific expression in ADL neurons (Fig. 7d).”.\nFigure 7d describes expression of 7TM receptor-encoding genes, sri-19 in ADL neuron, which is annotated based on\nposition and scRNAseq data from Reference 53. However, the manuscript lacks a description of how the annotation of cells\nbased on position was executed. If promoter-driven fluorescence proteins were used as comparative markers for this\nannotation, it would be helpful for the authors to include this information.\n17. Text line 240 “Additionally, the expression of the srr-6 receptor in neurons of the retrovesicular ganglion (RVG),\nalimentary tract, and excretory system (Fig. 7l), as well as the expression of sri-36 and sri-39 in the alimentary tract (Fig. 7h),\nsuggest that one or more of these tissues may also play a role in regulating exopher production in muscles.”.\nBased on the current experimental results, the claim that these tissues are involved in the regulation of exopher production\nmay need to be presented with more caution. Or, providing stronger supporting evidence, such as a rescue experiment,\ncould help substantiate this interpretation.\n18. Text line 247 “we aimed to investigate the underlying reasons for the release of these extracellular vesicles when worms\ndetect the pathogen in their environment.”.\nThe results in figure 8 are deciphering the effect of released exophers, not underlying reason (or cause) of released\nexophers.\n19. Text line 252 “To further explore this, …”.\nIt is difficult to follow what “this” is referring to. To improve clarity and ensure the narrative is easily understandable,\nspecifying explicitly what 'this' will be helpful.\n20. The authors describe the age synchronization of animals by isolating embryos at the pretzel-stage or 3-fold stage.\nTo enhance readability and accessibility, especially for readers not familiar with C. elegans development, it is recommended to\nstandardize the terminology used to describe these stages, or clarify if they refer to the same developmental stage.\nAdditionally, including a brief description of the method used for isolating pretzel-stage embryos would further aid in\nunderstanding.\n21. Figure 8b. It is ambiguous in this figure whether “+ PA14” in inlet legend indicates exposure to pathogen volatile before\nassay, or exposure to pathogen during survival rate assay.\n22. The explanation provided for Figure 8e and f in the current manuscript is insufficient. Details regarding the treatment of\nF1 animals during the experiment remain unclear, even with the provided illustration in Figure 8a. Including a more detailed\nexplanation of the experimental procedures would significantly enhance the readers' understanding.\n23. Text line 293 “1. Pathogen-induced exopher production: Exposure to live Pseudomonas aeruginosa PA14 or Serratia\nmarcescens Db10 induces exopher production in C. elegans body wall muscles.”\nIn Figure 9, this fact is indicated by the green upward arrows, but it should be more stressed because it is the main aspect\nstudied in this work.\n24. Text line 312 “Our findings suggest that, although exophers produced in response to different stimuli may appear similar\nin number, the distinct signalling pathways involved indicate potential differences in their roles or contents.”\nAlthough the research has thoroughly explored the mechanisms underlying exopher production in response to various\npathogen stimuli, there is no positive reason for assuming differences in their roles and contents. Thus, the work does not\n\"indicate\" such potential.\n25. A reference is required at text line 344 where it states 'In previous studies.'\n26. Text line 347 “The involvement of multiple G protein-coupled receptors (GPCRs) in regulating exopher production\nsuggests that exophergenesis is not triggered by a single metabolite but by a complex cocktail of pathogen-derived signals.”.\nActually, that might not be the only explanation. There are other possibilities to consider, for example, that the GPCRs are\nresponding to the same substances.\n27. Text line 354 “exophers and other EVs”\nGiven that this research has not evaluated other types of EVs, it is challenging to conclude that the other EVs are crucial in\nmediating the organism’s response to environmental stressors.\n28. Text line 416 \"(references)\"\nNeeds be replaced.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "In the manuscipt by Kołodziejska et al, the authors track the effects of exposure to pathogenic bacteria on production of muscle-derived giant vesicles (exophers). The authors find that exposure to Pseudomonas and Serratia pathogenic bacteria increases exopher production rate. Effects of signaling pathways that can impact innate immunity were shown, with Insulin-like signaling pathway mutant daf-16 reducing exopher production in all bacterial backgrounds, pathogenic and control. Its negative regulator akt-1 is tested, which might be expected to further increase exopher rates upon exposure to PA14 and Db10, but one cannot tell given the statistics shown. Please add such analysis. The authors should also acknowledge that these signaling pathways are not exclusive to innate immunity and could mediate exopher effects via other changes to the animals independent from immunity.\ntir-1 mutants affecting the p38 MAPK signaling pathway appeared to increase exopher production on OP50 (Fig 1d). It is unclear if tir-1 further increases PA14 and Db10 effects (Fig1f) since the comparison to WT was not statistically tested. In addition, the OP50 result appears different in the two panels. Fig 1d shows tir-1 mutants increasing exopher production on OP50, while Fig 1f appears to show no effect of the same experiment (although the statistical comparison vs WT is not shown). pmk-1 mutants in the same p38 pathway did not affect exopher levels on OP50 or suppress PA14 or Db10 driven increases. The way the comparisons are done does not allow the reader to tell if tir-1 mutants further increase PA14/Db10 effects. Please add the relevant statistical comparisons.\nThere are similar problems with interpretation for the other mutants dbl-1 and cul-6 on PA14 and Db10, as they are only statistically tested against OP50, but not against WT exposed to the same bacteria. This should be tested.\nPseudomonas PA14 mediated increases in muscle exopher production could be induced by non-volatile and volatile metabolites, with clear genetic differences in response to these different stimuli. They also differ in neuronal requirements. Volatile exposure to PA14 produced some egg retention (a known exopher inducer) while non-volatile metabolites (conditioned media) did not affect egg retention. The authors should modify lines 127-129 “This indicates that the P. aeruginosa-dependent increase in exopher production operates independently of the previously described embryo-maternal signalling “ accodingly. Fig 1 showed that Db10 exposure also produced egg retention. PA14 and Db10 effects could be further tested using sterile animals to determine if exposure can overcome empty uterus effects.\ndbl-1 mutant appears to suppress exopher production on OP50 control and partially suppress PA14 volatile effects (Fig 3a). Please add appropriates statistical test for this and modify accordingly line 121: “Therefore, the pathogen-induced EV modulation does not rely on canonical immune response pathways.” The effects on OP50 control make overall interpretation for dbl-1 difficult, although some studies suggest that OP50 is itself mildly pathogenic.\nThe authors test for effects of neuron ablation seeking to gain insight into sensing and propagating effects of bacterial metabolites. ADL, ASK, or AWC neurons were important for PA14 response in volatile and non-volatile assays. There is also some issue with interpretation here because these ablations also appeared to block most exopher production on OP50 control. If the neuron (or neuronal receptor such as npr-9) is required for basal exopher production it is difficult to know if it is directly involved in metabolite sensing and downstream signaling or if it is just generally required for exopher production. Please add statistical tests comparing samples exposed to the same bacteria but with intact vs ablated neurons.\nThe previously shown requirement for ASK in pheromone-mediated exopher production also clouds interpretation, although this is mitigated by lack of requirement for AQR/PQR/URX that are important for pheromone response.\nThe authors argue for a connection between volatile metabolite exposure, exopher production, and survival of P0 and F1 generations upon full PA14 exposure. They show that P0 exposure to PA14 volatile metabolites exhibited reduced survival of P0’s during bacterial infection, inversely correlated with exopher production. They also showed that worms with ablated ASK neurons, that produce fewer exophers than wild type worms, survive PA14 infection longer than wild type. They also showed that knockdown of the RME-2 receptor, which produce very few exophers, also survive P. aeruginosa infection longer than wild-type worms. They also found that sri-19 mutants, which do not show increased exopher production upon contact with non-volatile metabolites, survived significantly longer during infection. These are very interesting results. The authors also found interesting results for the F1 generation, with high P0 exopher generation correlated with F1 animals with improved survival on PA14. Overall interpretation is still somewhat limited for these results as they remain correlations. The authors should test if these perturbations affect embryo retention in the uterus. Effects on reproduction could be controlling exopher level rather than exopher level controlling reproduction. rme-2 is certainly very important for brood size.\nThe paper does not characterize which muscles produce exophers in response to pathogens. Do exophers appear randomly from all body-wall muscle, or is production limited to a particular body region, for instance near the uterus?\nThe authors should more directly compare their results here with those from their recent paper on pheromone-induced exophers.\nHave the authors tested OP50 conditioned media in the non-volatile experiments? It appears they used simple LB as a control rather than control conditioned media.\nPlease check Materials and Methods for accuracy. No micrographs are shown in this paper, but they are discussed in M&M.\nFig 1C should show negative regulation of DAF-16 by AKT.\nWhy do Figures 1i and 2c seem in conflict?\nFig 8 Legend is overstated: “Exophers levels are affecting survival rate post-infection.” This implies cause-and-effect, which is not demonstrated. A more accurate title would be “Exophers levels correlate or inversely correlate with survival rate post-infection.”\nIn many experiments the changes emphasized in the interpretations are statistically significant but represent a small change, in some cases a difference in exopher number from 9 to 11 or 7 to 10 is statistically significant while other experiments conclude no significance between similar median comparisons, 11 to 13 (Fig 3B). Which cases are biologically important differences? Overall, the statistics are misleading, graphs and text should indicate mean values for each experiment with standard error of the mean. In this current submission, the authors display interquartile ranges emphasizing the range around the median and are most appropriately used with skewed datasets that contain outliers (while these datasets appear to be normally distributed, with no outliers indicated). Moreover, precise trial numbers and sample sizes are not provided for each experiment (often a range is given) and several experiments in Fig 1 only have two biological replicates rather than the standard minimum of three. It is not clear from the text or figure legends if all data is shown, or if one representative dataset is shown in the main figure. Replicate experiments should be provided in the supplement to allow for data transparency regarding natural variation between experiments. Furthermore, it might be appropriate to evaluate these data as log fold changes rather than comparing averages to more rigorously determine if these small differences are meaningful, the authors should consult a biostatistician to guide them in this analysis.\nOverstatement: line 265-266 “Given that muscle exophers have been shown to improve animal reproduction and boost offspring development”. Previous work showed a correlation, not a cause-and-effect relationship.\nThe model at the end of Results should be in the Discussion.\nSeveral mutants in the TGF-Beta pathway have organismal-wide phenotypes including small body size (DBL-1). Data examining this mutant for exophers should be normalized to account for the difference in body size between the WT and dbl-1(nk3) animals.\nAdditional controls should be performed to address the effect of dietary restriction on muscle exophers (a known effector of egg retention and exophers in other tissues). Both volatile and non-volatile metabolites could have a profound impact on feeding which in turn would muddy the conclusions from these experiments and need to be addressed experimentally.\nSummary tables for P-values are nice. They could be improved by including the WT control alongside experimental results (Fig 5D).\nFig 7e – The legend states worms lacking SRI-36 and SRI-39 receptors are comparable to WT but data shown reports a significant difference (p=0.0016) between WT and sri-36/39(wwa57) mutants. This result is at odds with both the main text and the figure legend.", "reviewer_5": "The manuscript provides valuable insights into extracellular vesicle (EV) production in response to pathogen-derived metabolites. It highlights a regulatory network influenced by volatile and non-volatile metabolites, with implications for host-pathogen signaling and innate immunity. While the study is innovative and relevant, several areas require clarification and additional data to strengthen its impact.\n1. The study mentions key immune pathways such as insulin, TGFβ, p38 MAPK, and IPR, but excludes other established regulators like SKN-1, ELT-2, and HLH-30. Exploring their roles could enhance the analysis and provide a more comprehensive understanding of the mechanisms driving EV production. The selection criteria for these pathways should be justified.\n2. Figures 1D and 1F show inconsistent trends in EV production among mutants, such as tir-1(tm3036) and dbl-1(nk3). These discrepancies need clarification to ensure the validity of the conclusions drawn from these experiments. Graphical improvements, such as merging related panels or adding clearer annotations, would improve readability.\n3. Tissue-specific roles of key regulators like NPR-9 and GPCRs (e.g., SRI-19, SRI-36, SRI-39, and SRR-6) in immune activation and exopher production should be further investigated. Rescue experiments could identify their tissue-specific functions, providing insights into their biological significance.\n4. While the study demonstrates offspring survival benefits linked to increased maternal exospher production, it does not explore these effects beyond the F1 generation. The authors might want to investigate potential intergenerational transmission into the F2 generation.\n5. The specificity of the observed EV responses to pathogens versus general stressors remains unclear. Including controls for non-pathogenic stressors would help establish whether the responses are pathogen-specific.\nMinor Comments\n1. The Introduction contains some redundancy between the second and third paragraphs, particularly in discussing the advantages of using C. elegans as a model organism. Streamlining this section would enhance conciseness.\n2. Several references lack complete citation details, such as volume, page numbers, or correct publication years (e.g., reference #3 and #42).\n3. Minor typographical errors, such as missing punctuation on line 194, should be corrected to improve overall readability.", "reviewer_6": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "In this manuscript by Kołodziejska et al., the authors found that both the volatile and non-volatile pathogen\nmetabolites stimulate exophers generation in C. elegans. They dissected the chemosensation of volatile and\nnon-volatile pathogen metabolites, including the chemosensory neurons as well as the potential GPCRs\ninvolved, and proposed the sensory signals are integrated by the AIB interneuron via NPR-9. Finally, they\nproposed the significance of such regulation in enhancing offspring survival against pathogen in the basis of\ncompromising maternal survival. This work addresses an important mechanism on how species fight against\npathogen infection in the aspect of population level, and unravelled the potential mechanism of metabolites\nperception. Besides, the manuscript is clearly written with a clear logical flow. However, there is still critical\nevidence lacking, that should be completed before publication:\n1. Whether the regulation of exopher genesis in muscle is similar as in other tissue, such as neurons?\nResponse: Thank you for this valuable suggestion. To address it, we directly tested whether\npathogen-derived metabolites regulate exopher formation in mechanosensory neurons. As\npresented in the revised Results (Supplementary Fig. 2c and f), exposure to P. aeruginosa volatile\nmetabolites elicited a significant increase in neuronal exopher production, whereas non-volatile\nsecretome had no effect. These findings demonstrate that, unlike muscle exophers, which respond\nto both cue types, neuronal exophers are selectively driven by volatile signals.\n2. How do the metabolites sensed by the chemosensory neurons and integrated by AIB neurons pass to muscle\ncells? What molecular mechanisms mediate this intercellular communication?\nResponse: We appreciate the reviewer’s interest in the pathway linking chemosensory detection to\nmuscle‑cell exopher formation. Although it might be tempting to imagine that pathogen‑derived\nmetabolites are directly shuttled from sensory endings to muscle cells, this is unlikely given their\nchemical diversity and the spatial separation of these tissues. Instead, two other scenarios are more\nplausible:\n1. Classical neurotransmitters or neuropeptides released at synapses downstream of the\nprimary sensory neurons would traverse the interneuron network, ultimately modulating the\nneuromuscular junction, to trigger exophergenesis in body wall muscle.\n2. Long‑range neuropeptides secreted by integrative interneurons (such as AIB, AIA or RMG)\nwould diffuse or be transported through the pseudocoelom to reach muscle cells directly and\ninduce exopher production.\nDistinguishing between these mechanisms would require extensive follow‑up experiments, such as\ntissue‑specific knockouts of individual neuropeptide genes, conditional blockade of synaptic release,\nor peptide‑receptor mapping in muscle, which are beyond the scope of the present study.\nAccordingly, we instead focused our efforts on further mapping the sensory-to‑interneuron circuit:\nadditionally we show that ASJ sensory neuron is not involved (Fig. 5a - c), whereas AIA and RMG\ninterneurons both participate (Fig. 6e - k). We furthermore identified tripeptide isoleucyl-prolyl-proline\nas one of the PA14 non-volatile metabolite driving exopher upregulation (Fig. 4). Therefore, by\nclarifying the chemosensory and interneuronal components of this pathway, our work lays the\nfoundation for future studies on the synaptic and peptidergic signalling that convey environmental\ninformation to muscle cells.\nINSTITUTE OF BIOCHEMISTRY AND BIOPHYSICS www.ibb.edu.pl secretariate@ibb.waw.pl Page 2 of 32\nPOLISH ACADEMY OF SCIENCES Tel.: +48 22 592 21 45"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have made tremendous efforts during the revision process to address the questions raised by the reviewers, and overall they have successfully addressed most of my concerns. However, several minor points still need to be revised before publication:\n1. I agree with the other reviewer that representative images of muscle-derived exophers should be included in Figure 1.\n2. The authors should clarify how they confirmed that sri-19 is expressed in ADL neurons, and sri-36/39 in ASI and SKI neurons, in the absence of specific markers.\n3. Regarding my previous question (#5) on rescuing SRI-19 in ADL neurons: although the authors attempted rescue experiments, the results were unexpected. I appreciate that they have already made an effort, but since the evidence for SRI-19 function in ADL neurons remains inconclusive, the authors should either (i) use an ADL reporter to demonstrate co-localization with wrmScarlet–SRI-19 fusion protein, or (ii) confirm differential wrmScarlet–SRI-19 expression in wild-type animals with varying exopher numbers.\n4. In Figure 3b (middle panel), there is a clear trend toward increased exopher production in pmk-1 mutants upon PA14 non-volatile excretome treatment, although the difference is not statistically significant. The authors should increase the sample size (N) to clarify this effect.\n5. Baseline levels appear inconsistent across figures. For example, in Figure 6f and 6g, the wild-type values differ markedly (~8 vs. ~2). A similar issue is present in Figure 5a, where the wild-type values vary across panels. The authors should repeat the experiments or reasonably address these discrepancies.\n6. The lack of an additive effect between volatile and non-volatile metabolites should be discussed explicitly.\n7. I agree with the other reviewer that a brief description of the genetic ablation methods should be included in the Methods section, even if a citation is provided.\n8. I recommend revising the title. Since the study includes both volatile and non-volatile metabolites, the title should reflect both.\n9. I also recommend revising the abstract. The current version is overly long and complex, and a more concise version would improve clarity and impact.", "reviewer_2": "Second Review report for manuscript “Pathogen threat proximity shapes host extracellular vesicle production in pre-infection\nresponse”\n(Remarks to the Authors)\nUpon revision, authors added considerable amount of new data and new figures, which is admirable along with the efforts already put in the original submission. On the contrary, it became clearer through one round of review and revision that authors have a strong attitude to promote their hypothesis, or belief, in a biased way and \"cherry-pick\" the results to support the hypothesis as described below.\nMajor comments:\n1. Reproducibility of the results\nIn response to our previous comment 13, authors provided a transparent explanation about methodological differences\nbetween Figure 1d and Figure 1e-g, which can reasonably account for the mutant phenotype discrepancies between these\nfigures. However, a closer look at the data within the main text raises additional concerns.\nQuestion 1: How can baseline exopher production be compared between strains?\nAuthors explained in their rebuttal as follows:\n\"In Fig. 1e – g, worms, and their OP50 controls, were subjected to an additional 3‑hour incubation at 25 °C during the\ninfection window....\", \"Furthermore, Fig. 1e – g exophers were scored on worms immobilized on agar pads for imaging under\nDr. Pujol’s microscope,....\", \"all other experiments involving muscle exophers presented in this manuscript, including those\nin Fig. 1d, were conducted on freely moving animals.\"\nAssuming all experiments except Fig. 1e-g were conducted under the same conditions, as also described in Methods, we\nnote that even in the wild type, baseline data (unexposed control, namely exposed to OP50 alone) are variable between\nexperiments if we compare across all figures (for instance Fig. 5a, b, right panel, Fig. 6a, g, i, j, etc).\nThis raises a fundamental question: What is the source of this variability, and which parts of the results are reproducible and\ntrustable? If the main source of variability is a day-to-day fluctuation, the next question is whether baseline exopher\nproduction can be reproducibly compared between different strains when the experiments are conducted on the same days.\nIf we look at the unexposed controls in Fig. 3, daf-16, for example, do not look different from wild type in Fig. 3a/b and tir-1 in\nFig. 3a do not look different from wild type. On the other hand, akt-1 looks very different in both figures. These results are not\nconsistent with Fig. 1d, where daf-16 and tir-1 are significantly different from wild type but akt-1 is not. Authors describe N=3\nfor Fig. 3a, and N=3-4 for Fig. 3b, implying not all experiments in Fig. 3 were conducted on the same days. Then how does\nthe baseline data look like if only experiments conducted on the same days are compared between different strains? Does it\nstill fail to reproduce Fig. 1d?\nUpon revision, Fig. 8e was replaced from the previous version (Fig. 7e). The data points themselves for all three lines\nappear to have been altered or added, and the sample size has changed from \"n = 90, N = 3 independent experiments\" to \"n\n= 90-180, N = 3-6 independent experiments\", implying authors conducted additional experiments, and the results of the\nstatistical test changed. This also illustrates the variability between experiments and its effect on the conclusion.\nIn summary, if inter-strain comparison between strains is difficult even when experiments are conducted on the same days,\nthe only solution will be to make judgements from sufficient numbers of independent experiments. Considering the above,\nN=3 does not seem enough for these tests.\nQuestion 2: How can fold-change induction in exopher production be compared between strains?\nAuthors commented in their rebuttal that \"despite these differences in absolute numbers, the relative increases in exopher\nproduction upon pathogen exposure remain highly reproducible\", and that \"each experiment includes internal E. coli OP50\ncontrols, ensuring that our conclusions are based on fold‑change induction rather than raw baseline values\".\nThis may be true, but would authors be able to show numerically that fold-change is more stable than baseline, for example\nby combining all wild type data?\nIf this claim holds true, one option would be to avoid comparing the baseline between strains and focus on\ncomparing the fold-change induction. Further, if the fold-change comparison between unexposed/exposed pairs that stem from the same\nculture turns out most stable, authors can change the statistical tests so as to compare the (same-culture) fold-change values\nbetween strains.\nAdopting this option will also necessitate the removal of a number of figures and claims. For example,\ncomparisons of baseline values such as Fig. 1d and Fig. 8a, e, i, won't be attempted and deleted from the\nfigures, because, as discussed above, these data are not reliable without sufficient N. Upon revision, authors\nadded Supplementary Figs. 1a, b, 3, 4, 5 and 7, in which they extracted only volatile/nonvolatile-exposed data\nfrom Figs. 1, 3, 5, 6 and 8, respectively, and compared them statistically. Based on this, authors made new\nclaims such as involvement of sri-19 in the volatile signaling. However, if authors admit that baseline is\nvariable and only fold-change is reliable, comparisons between induced values alone are not\nmeaningful. Accordingly, in this case Supplementary Figs. 1a, b, 3, 4, 5 7 and their related statements (such as asserted\nmodulatory roles of pmk-1, akt-1 and AQR/PQR/URX) need to be removed.\nAs a summary, it is important to evaluate which aspect of the exopher induction by the pathogen-derived\nstimulus is numerically reproducible. Based on the evaluation, authors need to report only highly stable and\nreproducible data and base their discussion on them.\n2. Functional roles of exopher induction\na. Does the P0-F1 trade off exist?\nIn response to multiple review comments regarding previous Fig. 8, authors replaced the results with those from a new set of\nexperiments. At 20°C (Fig. 9), the data showed that only volatile metabolites improve F1 survival in an SRI-19-dependent\nmanner, with only a \"slight nonsignificant decrease\" in P0 survival. In contrast, at 25°C (Supplementary Fig. 8), it is shown\nthat volatile metabolites have no effect on F1 survival but reduce P0 survival. Additionally, non-volatile secretomes reduced\nF1 survival but had no effect on P0 survival at 25°C. Based on the data, the direct correlation between P0 and F1 fitness,\nwhich is a key premise of the paper's overarching narrative, appears to be nonexistent. The data do not consistently show that\nincreased exopher production strengthens offspring pathogen resistance, nor do they consistently show that it\nweakens it. Instead, the effects are highly dependent on specific conditions (volatile vs. non-volatile cues and\ntemperature), with no clear trade-off between maternal sacrifice and offspring fitness. It is necessary to\nthoroughly revise the manuscript, for example the language in the abstract such as \"significantly boosts\noffspring fitness... at the cost of maternal survival…\" and “to optimize survival across generations”, to reflect\nthese results accurately.\nb. Is exopher involved in the regulation of pathogen resistance?\nThe inconsistencies also affect the interpretation of functional roles of exophers. At 20°C (Fig. 9), the data showed that only\nvolatile metabolites improve F1 survival in an SRI-19-dependent manner. This finding is interpreted by the authors as\nevidence for the functional role of exopher induction in improving F1 survival. However, as SRI-19 protein structure and\nexpression pattern suggested, it is likely to be a sensory receptor or its modifier. Therefore, the F1 survival effect could be\nmediated through SRI-19-dependent signaling pathway that operates independently of exopher production.\nThe authors' claims are further undermined by inconsistencies in their experimental design and data\ninterpretation. They state that the inability of exopher upregulation due to a lack of sri-19 is related to reduced\nembryo accumulation and prolonged survival upon exposure to PA14 non-volatile secretomes at 25°C (Text\nline 424-, line 433-). However, the exopher phenotype for sri-19 mutants under this 25°C condition was never\nactually observed. The authors instead rely on data from a different temperature (20°C) to support their claim.\nThis conclusion cannot be drawn from the results provided, as an increased temperature not only changes the\nresponse of C. elegans to P. aeruginosa infection but also enhances exopher production. Therefore, using\nresults from a different temperature for this assertion is logically flawed. In addition, only volatile metabolite\nimproves F1 survival, while sri-19's involvement in the regulation of exopher induction in response to the\nvolatile metabolites, newly asserted based on Supplementary Fig. 7a, is based on inappropriate comparisons\nas discussed in point 1 above (ignoring baseline instability; exophers are still increased by volatile\nmetabolites, Fig. 8b).\nAuthors presented data showing that unlike wild type, rme-2 P0 becomes more resistant to PA14 pathogen infection.\nThis could be a direct consequence of reduced number of embryos but not necessarily due to the lack\nof exophers.\nOverall, evidence on the biological role of exopher is very weak, and overstatement on it should be carefully\navoided.\nMinor comments:\n1. Regarding the response to comment 12, unlike the authors’ response, the limitation is not discussed in the\nDiscussion section. On the contrary, they rather emphasize the effect of the non-volatile secretome and volatile\nmetabolites in delivering accurate information of pathogen proximity in Text line 445. Acknowledging the\nlimitations is required for clarity. Authors only showed that volatile metabolites and non-volatile secretome\nare sensed through different molecular pathways to increase muscle exopher production. Let alone it is\nunknown whether the contents of these exophers are different, it is unclear whether these different cues cause\ndifferent consequences through the exophers (for example regarding pathogen tolerance of P0 and F1 as\ndiscussed above). The text at line 100 \"Our research demonstrates that worms can differentiate the proximity\nof a pathogen threat based on the type of compound they detect\", which remains unchanged from the original\nmanuscript, is clearly an overstatement; the presented results DO NOT show \"worms can differentiate the\nproximity\". This and related statements need to be moved to Discussion\n2. Response to comment 17. While the revised text on lines 215-219 acknowledges the potential for\nredundancy or compensation, the subsequent statement on lines 219-223 appears to contradict this, strongly\nsuggesting that the insulin signaling pathway is not involved in exopher production induced by non-volatile\nsecretomes. Also, the authors claim that “non‑volatile secretome‑driven upregulation selectively requires\nTGFβ, p38 MAPK, and IPR pathways” on Text line 230-231. These conclusions are still not supported by the\nprovided data. At the minimum, \"by itself\" need to be inserted after \"insulin pathway does not\" at line 221,\nand \"selectively\" at line 231 need to be removed.\n3. Response to comment 43 and Text line 542. Addition of the data upon revision on neuronal exopher is informative.\nHowever, the manuscript's narrow focus on exophers makes it difficult to support the broader\nclaim regarding a possible hormetic role of EVs in general. The discussion is required to be limited to the\nspecific findings on exophers.\n4. Figure 2b. Please describe how the authors identified the region of coelomocytes.\n5. Text line 487-495. This paragraph of the Discussion section presents a broad conclusion about the\nprinciples of sensory neuroscience in C. elegans, referring to concepts such as \"combinatorial coding\" and\nthe interpretation of \"unique activation patterns across multiple neurons\". However, these conclusions are not\nsupported by the data presented in the manuscript. The study does not include any experiments that directly\nmeasure neuronal activity or the circuit relationships that process the sensory information.\n6. Text line 499-502. The authors state that this research addresses the ASK neuron's participation in a\npathway related to maternal survival upon pathogen exposure. However, the data demonstrating effect of ASK\nremoval in maternal survival upon pathogen exposure (previous Fig. 8b) does not exist in the current\nmanuscript. Thus, this could not be discussed in the current manuscript.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "My concerns have been well addressed.", "reviewer_5": "The revision addresses several of my points, including clarifying figure inconsistencies, adding tissue-specific rescue data, and correcting the writing and references. I appreciate these efforts. Two concerns remain: the omission of key immune regulators (SKN-1, ELT-2, HLH-30) without justification, and the lack of testing beyond the F1 generation. The question of pathogen specificity is improved by the starvation controls but would be stronger with non-pathogenic stressors. Overall, the manuscript is much improved.", "reviewer_6": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We sincerely thank the reviewers for their constructive comments, which have greatly improved our\nmanuscript, and we are pleased to present this revised version.\nPlease find a detailed description of the edited paragraphs below (the reviewers’ comments are in italics and\nour responses are in blue font):\nReviewer #1 (Remarks to the Author):\nThe authors have made tremendous efforts during the revision process to address the questions raised by the\nreviewers, and overall they have successfully addressed most of my concerns. However, several minor points\nstill need to be revised before publication:\n1. I agree with the other reviewer that representative images of muscle-derived exophers should be included\nin Figure 1.\nResponse: Thank you for this valuable suggestion. In response, we have added an example of a\nmuscle-derived exopher produced by C. elegans in Fig. 1a.\n2. The authors should clarify how they confirmed that sri-19 is expressed in ADL neurons, and sri-36/39 in\nASI and SKI neurons, in the absence of specific markers.\n3. Regarding my previous question (#5) on rescuing SRI-19 in ADL neurons: although the authors attempted\nrescue experiments, the results were unexpected. I appreciate that they have already made an effort, but since\nthe evidence for SRI-19 function in ADL neurons remains inconclusive, the authors should either (i) use an\nADL reporter to demonstrate co-localization with wrmScarlet–SRI-19 fusion protein, or (ii) confirm\ndifferential wrmScarlet–SRI-19 expression in wild-type animals with varying exopher numbers.\nResponse: We thank the reviewer for these comments. As indicated in the previous version of the\nmanuscript we confirmed sri-19 expression in ADL neurons experimentally: the SRI-19::wrmScarlet\nfusion protein co-localizes with the gap-15p::GFP reporter, which marks ADL neurons\n(Supplementary Fig. 7i). Moreover, single-cell RNA-seq data from CeNGEN (CeNGENApp) show\nthat sri-19 is predominantly expressed in ADL sensory neurons, with additional expression detected\nin PHA and URY neurons (Supplementary Fig. 7h). Together, these data support sri-19 expression\nin ADL neurons and strengthen our conclusion regarding its neuronal specificity.\nRegarding sri-36 and sri-39 expression, our conclusions are based on previously published data\n(Vidal et al., PLOS Biology, 2018, “An atlas of Caenorhabditis elegans chemoreceptor expression”)\nand on the anatomical position of the corresponding cells within the C. elegans nervous system, as\ndescribed in the legend of Fig. 8h.\n4. In Figure 3b (middle panel), there is a clear trend toward increased exopher production in pmk-1 mutants\nupon PA14 non-volatile excretome treatment, although the difference is not statistically significant. The\nauthors should increase the sample size (N) to clarify this effect.\nINSTITUTE OF BIOCHEMISTRY AND BIOPHYSICS www.ibb.edu.pl secretariate@ibb.waw.pl Page 1 of 8\nPOLISH ACADEMY OF SCIENCES Tel.: +48 22 592 21 45"}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed all of my concerns. I have no further comments, and I recommend acceptance of the manuscript.", "reviewer_2": "The authors have addressed many of the points raised in the previous review, particularly regarding the inconsistencies and textual corrections. However, two concerns remain:\n1) Response to comment 10. The clarification regarding the use of different transgenes for exopher visualization addresses concerns regarding the baseline variability observed in Figures 5 and 6. However, the concern regarding Figure 3 remains unresolved. Since the mutant strains in Figure 3 (excluding pmk-1 and cul-6) utilize the same transgene background as those in Figure 1d (wacIs1 and wacIs14), they should be directly comparable. The relationship of baseline between wildtypes and the mutants differs clearly between Figure 1d and Figure 3a left panel (e.g., daf-16, tir-1 and akt-1). The provided explanation about different transgenes does not account for this specific inconsistency. Although it is the authors' full responsibility to deal with this issue, as a possible option, modifying “all” to “some” at line 114-115 could more accurately reflect the complexity of the results.\n2) Regarding Figure 1a, while the inclusion of representative images helps readers visualize the muscle-derived exophers, the current figure composition is difficult to interpret. Specifically, the fourth and fifth panels appear distinct from the first three. However, the manuscript and figure legend lack a description explaining their significance or how to interpret the data, particularly the heatmap in the fifth panel. Adding a clear explanation of what these specific panels represent and what they are intended to convey would significantly improve reader understanding."}, "author_response": "We thank the Reviewer for this helpful comment. Following the Reviewer’s suggestion,\nwe have revised the sentence describing the data in Figure 1e to more accurately reflect the\ncomplexity of our results. The updated sentence now reads: “In some of the tested immune response\npathways, we observed altered levels of exophergenesis, either decreased or increased, compared\nto wild-type worms.”\n\nWe thank the Reviewer for drawing our attention to this point. To improve clarity, we\nhave expanded the figure legend for Figure 1a to provide a detailed explanation of each panel and\nits relevance. Specifically, we now clarify that all five panels originate from the same animal and\nwere generated from a single confocal z-stack. Panels (i–iii) present single focal plane of differential\ninterference contrast, overview fluorescence, and magnified views of mitochondria-containing\nexophers, respectively. Panels (iv) and (v) correspond to a 3D surface rendering and a depth-coded\nheatmap of the same z-stack, generated to visualize the spatial arrangement and extracellular\ntopology of exophers. The colour scale in the heatmap denotes depth within the volume, with cooler\ncolours indicating structures closer to the imaging plane and warmer colours representing deeper\nregions. These additions to the figure legend now explain the purpose and interpretation of each\npanel, improving figure readability and overall comprehension.\n\nWe sincerely thank the reviewers for their constructive comments."}]

Decision letter