# Pathogen threat proximity shapes host extracellular vesicle production in pre-infection response

Klaudia Kolodziejska, Agata Szczepanska, Nathalie Pujol, Wojciech Pokrzywa, Michal Turek

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Klaudia Kolodziejska, Agata Szczepanska, Nathalie Pujol, Wojciech Pokrzywa, Michal Turek. Pathogen threat proximity shapes host extracellular vesicle production in pre-infection response. 2024. [hal-04792559](https://hal.science/hal-04792559v1)

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1 Pathogen threat proximity shapes host extracellular vesicle

2 production in pre-infection response

3

4 Klaudia Kołodziejska¹, Agata Szczepańska¹, Nathalie Pujol², Wojciech Pokrzywa³, Michał

5 Turek¹

6

7 Affiliations:

8 ¹Laboratory of Animal Molecular Physiology, Institute of Biochemistry and Biophysics, Polish

9 Academy of Sciences, Warsaw, Poland

10 ²Aix Marseille Univ, INSERM, CNRS, CIML, Turing Centre for Living Systems, 163 Avenue de

11 Luminy, case 906, 13009 Marseille, France

12 ³Laboratory of Protein Metabolism, International Institute of Molecular and Cell Biology in

13 Warsaw, Poland

14

15 Correspondence should be directed to:

16 MT: m.turek@ibb.waw.pl

17
18 Abstract

19 Extracellular vesicles (EVs) play a crucial role in immune responses, yet it remains unclear
20 whether pathogen metabolites alone can stimulate EV production prior to infection. Using
21 *Caenorhabditis elegans*, we investigate this question through the lens of exophers – large,
22 evolutionarily conserved EVs known to enhance proteostasis, extend lifespan, and improve
23 reproductive fitness. Our study uncovers distinct regulatory mechanisms driving EV production
24 in response to pathogen-derived volatile and non-volatile metabolites, providing insights into
25 host-pathogen signaling before physical interaction. We reveal a sophisticated network that
26 adjusts EV production based on pathogen proximity: non-volatile metabolites, signaling an
27 immediate threat, activate immune-dependent EV pathways, while volatile metabolites,
28 forewarning potential danger, initiate immunity-independent exopher production. Both
29 responses rely on sensory neurons, with ASK, ADL, and AWC neurons playing central roles in
30 each, and additional input from ASI, AWB, and ASH neurons specifically enhancing non-
31 volatile-induced EV production. Multiple GPCRs, including SRI-19, SRI-36, SRI-39, and
32 SRR-6, are crucial for the non-volatile response, with signal integration mediated by the AIB
33 interneuron and NPR-9 receptor in both responses. Notably, volatile-induced exopher
34 production enhances offspring survival against pathogens but compromises maternal survival.
35 Thus, our study shows that *C. elegans* distinguishes pathogen proximity through metabolite
36 types, activating EV-dependent physiological responses tailored to either immediate or
37 anticipated threats to optimize survival across generations.
38

39

39 Keywords

40 *C. elegans*, extracellular vesicles, exophers, pathogens, immune response, olfactory neurons,
41 GPCRs

42
43 **Introduction**

44 Extracellular vesicles (EVs), including exosomes and microvesicles, are pivotal in the host
45 immune response by mediating intercellular communication and regulating immune functions.

46 Released by various cell types, EVs carry a diverse array of bioactive molecules such as
47 antigens, signalling molecules, and genetic material, thus influencing immune cell behaviour
48 and activity¹,². Pathogen-derived EVs often contain pathogen-associated molecular patterns
49 (PAMPs) that can activate immune responses³, while host-derived EVs help modulate
50 inflammation and immune activation, maintaining homeostasis and enhancing defence
51 mechanisms against pathogens⁴. These roles for EVs have been well-documented during active
52 infection, where pathogens are already invading the host. However, pathogens release both
53 volatile and non-volatile metabolites, which can alert and prepare the host to their exposure⁵,⁶.

54 Whether such metabolites can modulate EV production prior to infection is not known.

55 The nematode *Caenorhabditis elegans* is a widely used model for studying host-pathogen
56 interactions, particularly valuable for examining its responses to clinically significant human
57 pathogens such as *Pseudomonas aeruginosa*, *Serratia marcescens*, and *Staphylococcus
58 aureus*⁷. This organism offers several advantages due to its simplicity, genetic tractability, and
59 well-characterized immune responses. *C. elegans* relies solely on innate immune pathways,
60 making it an ideal organism for dissecting fundamental aspects of innate immunity without the
61 confounding influence of an adaptive immune system⁸. Additionally, its transparent body
62 allows real-time observation of infection processes, and its short lifespan and large brood size
63 enable high-throughput genetic and pharmacological screens⁹. The evolutionary conservation
64 of many immune pathways between *C. elegans* and higher organisms further enhances its
65 relevance for studying host-pathogen interactions¹⁰,¹¹.

66 *C. elegans* has emerged as well as a valuable model for studying EV production. Due to its
67 transparent body and well-characterized genetics, *C. elegans* allows to track EV production in
real-time and investigate the regulatory pathways involved¹². One of the examples of 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 reproduction¹³⁻¹⁸. Previous studies have demonstrated that exophers help protect neuronal activity in *C. elegans* by expelling toxic cellular debris¹³, a process also observed in mammals, where mouse cardiomyocytes release exophers to discard defective mitochondria, maintaining metabolic balance and preventing inflammation¹⁹. In addition to waste disposal, exophers have been shown to facilitate inter-tissue transport to facilitate reproductive fitness¹⁴, a process that can be regulated by social signalling derived from other animals within the population¹⁸.

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

Our study uncovers a complex regulatory network governing exopher production in *C. elegans*, shaped by the type of interaction with pathogens. Pathogen infection or exposure to their metabolites increases exopher production. However, the molecular mechanisms regulating volatile- and non-volatile metabolite-dependent increases in EV production are distinctly controlled at immune, sensory, and neuronal levels. Our research demonstrates that worms can differentiate the proximity of a pathogen threat based on the type of metabolites they detect. Non-volatile metabolites, typically sensed at close range, signal the pathogen's immediate presence, whereas volatile metabolites, detected from a greater distance, indicate a nearby pathogen that may pose a lower threat. This ability to distinguish between signals triggers a
context-specific physiological response, which may or may not involve immune activation,
depending on the nature of the detected metabolites. These findings provide new insights into
the physiological mechanisms of EV production in *C. elegans* and suggest that similar
mechanisms may be conserved across species.

## 97 Results

## 98 Infection with pathogens induces exopher production in hermaphrodite muscles

To verify if pathogen infection influence production of extracellular vesicles in *C. elegans*, 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 hour later we examined the number of
exophers released by body wall muscles (BWMs) in a similar way as described before²⁰ (Fig.
1a). 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. 1b).

Given that extracellular vesicles in other organisms are often part of the immune response¹,²¹,
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 pathways²²,²³, including the
insulin pathway (*akt-1*, *daf-16*)²⁴, TGFβ pathway (*dbl-1*)²⁵, p38 MAPK pathway (*tir-1*, *pmk-1*)²⁶,²⁷, and Intracellular Pathogen Response (IPR) pathway (*cul-6*)²⁸,²⁹ (Fig. 1c). In all 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* bacteria after knocking out at least one component of each pathway
(Fig. 1d). However, when immune response mutants were exposed to pathogens, there was a
consistent increase in exopher production across all tested mutants, as observed in wild-type
worms (Fig. 1e-g). The exception was the *cul-6* mutant with a compromised IPR pathway, which showed a smaller increase in exopher production upon exposure to *P. aeruginosa* and a decrease in exopher production upon exposure to *S. marcescens* when compared to the wild-type control (Fig. 1h). Therefore, the pathogen-induced EV modulation does not rely on canonical immune response pathways.

Because it was shown previously that exopher production depends on the presence of embryos in the uterus<sup>14,30</sup>, we have tested whether exposing worms to pathogens causes increased eggs retention which in turns could be responsible for increased exopher production. Our results show that while we could observe increased eggs retention for worms exposed to *S. marcescens* Db10, there was no increase for worms exposed to *P. aeruginosa* PA14 (Fig. 1i). This indicates that the *P. aeruginosa*-dependent increase in exopher production operates independently of the previously described embryo-maternal signalling, suggesting the involvement of a novel regulatory pathway. It is possible that *S. marcescens*-mediated EV modulation also occurs via this pathway, but disentangling it from the embryo-maternal effect is more challenging. Therefore, we have focused our investigation exclusively on *P. aeruginosa* to uncover the mechanisms underlying pathogen-induced exopher production.

## Pathogen non-volatile and volatile metabolites trigger exopher production

Recent reports indicate that *C. elegans* can detect pathogen volatile metabolites, which influence their physiology in a cell non-autonomous manner<sup>31,32</sup>. Given that, we investigated whether exposure to pathogen odours alone would be sufficient to induce exopher production in muscle cells. To test this, we covered NGM plate seeded with OP50 and containing age-synchronized L4-stage worms with another 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
142 that exposure to *P. aeruginosa* volatile metabolites indeed induces exopher production (Fig. 2b) as well as causes embryo accumulation in utero (Fig. 2c).

144 Previous studies have shown that exposing *C. elegans* to *P. aeruginosa* metabolites leads to a robust immune response³³. Therefore, we aimed to determine whether the increased production of EVs in response to pathogens requires direct infection or if contact with bacterial metabolites is sufficient (Fig. 2d). As shown in Fig. 2e, direct infection with *P. aeruginosa* is not necessary; worms grown on plates with *P. aeruginosa* supernatant also produced more exophers. Notably, this increase in exopher production do not depend on increased egg retention in the worm's uterus (Fig. 2f).

151 Next, we investigated whether the increased EVs production in our new experimental setups is influenced by innate immunity signalling pathways. Our results indicate that none of the tested pathways—including insulin, TGFβ, p38 MAPK, and IPR—significantly contribute to the volatile metabolite-dependent increase in EV production (Fig. 3a and c). However, there is a notable discrepancy in the role of these pathways when considering the non-volatile metabolite-dependent increase in EV production. Specifically, while the insulin pathway does not appear to be involved, the TGFβ, p38 MAPK, and IPR pathways are essential for the supernatant-dependent increase in exopher production (Fig. 3b and c). These results suggest that *C. elegans* relies on distinct immune signalling mechanisms for EV production, activating TGFβ, p38 MAPK, and IPR pathways in response to direct contact with bacterial metabolites, while bypassing these pathways entirely for airborne signals.

162 **Multiple types of sensory neurons regulate exopher production in response to pathogen**
163 Olfactory neurons in *C. elegans* detect numerous environmental signals that influence various aspects of the worm's life, including behaviour, physiology, and reproduction³⁴. Additionally, our recent findings have shown that olfactory neurons regulate pheromone-dependent increases in EV production¹⁸. To identify the sensory neurons responsible for regulating the pathogen
supernatant-dependent and volatile metabolite-dependent increases in EV production, we
utilized nematodes with genetic ablations of sensory neurons known to mediate pathogen
recognition³⁵⁻³⁷. By systematically analysing the effects of these ablations, we discovered that
the removal of either ADL, ASK, or AWC neurons completely abolishes both supernatant-
dependent and volatile metabolite-dependent upregulation of exopher production (Fig. 4a-c).
Conversely, the removal of AQR/PQR/URX previously shown to be responsible for
exophergenesis regulation¹⁸ has no effect in either assay (Fig. 4a-c). Interestingly, we observed
discrepancies among ASI, ASH, and AWB neurons. While ASI, ASH, and AWB neurons are
crucial for the supernatant-induced increase they do not play a role in volatile metabolite-
dependent increase in EV production (Fig. 4a-c). These findings show that multiple types of
sensory neurons regulate exopher production in response to pathogen metabolites in a context-
dependent manner, with ADL, ASK, and AWC neurons playing pivotal roles.

AIB interneuron and AIB-specific NPR-9 receptor integrate sensory response to mediate
exopher production

To understand the neuronal circuit mediating pathogen-induced exopher production, we utilized
the available *C. elegans* connectome to search for an interneuron downstream of all sensory
neurons involved in this response³⁸. This search pinpointed the AIB interneuron, which has
previously been implicated in regulating *C. elegans* immunity³⁹. According to the same study,
the AIB-specific neuropeptide receptor NPR-9 mediates this immune response³⁹. Consequently,
we investigated the involvement of the AIB interneuron and the NPR-9 receptor in the
regulation of exopher production. Our data show that the genetic ablation of the AIB
interneuron does not alter exopher production under standard growing conditions, whereas the
removal of the NPR-9 receptor leads to a decrease in exopher production (Fig. 5a).
Additionally, upon exposing worms to *P. aeruginosa* metabolites, we found that the removal
of AIB neuron or NPR-9 receptor abolishes the increased exophergenesis induced by pathogen
volatile metabolites (Fig. 5b and e) and supernatant (Fig. 5d and e). These results suggest that the AIB interneuron and NPR-9 receptor are essential for mediating exopher production in response to pathogen signals

## Multiple G-protein coupled receptors control pathogen-induced exopher production

G-protein coupled receptors (GPCRs) are essential mediators that enable cells to interact with their environment by transmitting signals. In both vertebrates and in invertebrates, GPCRs play a key role in coordinating immune responses$^{40,41}$. In order to pinpoint the receptor(s) responsible for binding pathogen-released molecule(s) that modulate exophergenesis, we analysed published transcriptomics data from worms exposed to *P. aeruginosa* PA14 compared to worms grown on *E. coli* OP50$^{42}$. 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.$^{43}$, these GPCRs are expressed in ASK and ASI cells, which we have shown to play an important role in exopher upregulation (Fig. 3a-b). Additionally, our prior RNA sequencing, which identified the GPCR *str-173* as a regulator of socially mediated exopher production, also highlighted *sri-36* and *sri-39* as top candidates, further supporting their potential as strong candidates for validation$^{44}$. To investigate the roles of *sri-36* and *sri-39* in exopher regulation, we employed CRISPR/Cas9 technology to generate a mutant with a deletion encompassing both receptor-encoding genes, as they are located only 1.9 kb apart, with one gene situated between them (Supplementary Fig. 1).

Moreover, to identify receptors that regulate exophergenesis and may play a role in stimulating exopher production (potentially through pathogen metabolites), we conducted RNA sequencing on age-synchronized wild-type worms that exhibited either many (more than 20) or few (fewer than 2) 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 variation$^{45}$. The results of this RNA sequencing show that worms producing many
217 exophers differ significantly at the transcriptomic level from worms producing few exophers
218 (Fig. 6a). Specifically, 609 genes were upregulated and 665 genes were downregulated (p adj
219 < 0.05; -1> log2 fold change > 1) (Fig. 6b and Supplementary Data 1). Among the statistically
220 significant GO terms, "cilium assembly" was upregulated in worms producing many exophers
221 (Fig. 6c). This finding aligns with our data showing that ciliated neurons are crucial for
222 regulating exorphogenesis in muscles (as it was previously shown in Szczepańska, Olek et al.⁴⁴).

223 Notably, three GPCRs—STR-173, SRR-6, and SRI-19—were significantly altered in animals
224 producing varying numbers of exophers (Fig. 6d). Importantly, we had previously identified
225 STR-173 as a GPCR regulating exorphogenesis via the male pheromone ascr#10, validating our
226 approach¹⁸. Therefore, we decided to create CRISPR/Cas9-mediated mutants for the *srr-6* and
227 *sri-19* genes encoding GPCRs as well (Supplementary Fig. 1).

228 Among the four GPCRs studied, the removal of each receptor significantly suppressed *P.*
229 *aeruginosa*-induced exopher production in response to bacterial supernatant (Fig. 7c, g, k), but
230 not to volatile metabolites (Fig. 7b, f, j). Notably, the basal level of exorphogenesis in GPCR
231 mutant worms under standard conditions remained unchanged (Fig. 7a, e, i). These findings
232 collectively indicate that these receptors are critical for pathogen-induced exopher production,
233 but not under non-stressed conditions.

234 The wrmScarlet CRISPR/Cas9-mediated transcriptional knock-in of the *sri-19* gene revealed
235 its specific expression in ADL neurons (Fig. 7d). Furthermore, transcriptional reporters using
236 fluorescent proteins for the *sri-36* and *sri-39* genes indicated expression in anterior ciliated
237 neurons (Fig. 7h), which, based on available literature⁴³, correspond to ASI and ASK neurons.

238 This observation is consistent with our data, underscoring the critical role of ADL, ASK, and
239 ASI neurons in pathogen-induced exopher production and establishing its molecular
240 mechanism. Additionally, the expression of the *srr-6* receptor in neurons of the retrovesicular
241 ganglion (RVG), alimentary tract, and excretory system (Fig. 7l), as well as the expression of
242 *sri-36* and *sri-39* in the alimentary tract (Fig. 7h), suggest that one or more of these tissues may
243 also play a role in regulating exopher production in muscles.

244 **Offspring of animals that produce more exophers after exposure to pathogen volatile**
245 **metabolites have a higher survival rate post-infection, at the cost of the mother's survival**
246 Building on our findings, which demonstrated an increase in exopher production in the presence
247 of pathogen volatile metabolites, we aimed to investigate the underlying reasons for the release
248 of these extracellular vesicles when worms detect the pathogen in their environment. In *C.
249 elegans* the tissues most frequently involved in host-pathogen defence are those exposed to the
250 environment: the epidermis and the intestine<sup>22,23</sup>. Therefore, it is unlikely that muscle-derived
251 exophers serve as carriers for immune pathway effectors, such as C-type lectins or antimicrobial
252 peptides, between tissues to enhance the immune response. To further explore this, we tested
253 whether worms that produce more exophers due to exposure to *P. aeruginosa* volatile
254 metabolites could survive *P. aeruginosa* infection for a longer period (Fig. 8a). Interestingly,
255 we observed that these worms exhibited reduced survival during bacterial infection, which
256 inversely correlates with exopher production (Fig. 8b). This result was further correlated by the
257 fact that worms with ablated ASK neurons, that produce fewer exophers than wild type worms
258 (Fig. 4a-b), survive *P. aeruginosa* infection longer than wild types (Fig. 8b). This also aligns
259 with the fact that worms with the knockdown of the RME-2 receptor, which produce very few
260 exophers<sup>14</sup>, also survive *P. aeruginosa* infection longer than wild-type worms (Fig. 8c). Thus,
261 it appears that worms producing many exophers after pre-exposure to pathogen volatile
262 metabolites exhibit worse survival during subsequent infection. Additionally, *sri-19* mutants,
263 which do not show increased exopher production upon contact with *P. aeruginosa* non-volatile
264 metabolites, survived significantly longer during infection (Fig. 8c) which demonstrates that on
265 mechanistic level survival is interconnected with the regulatory elements for EV production.
Given that muscle exophers have been shown to improve animal reproduction and boost offspring development, we hypothesized that worms producing more exophers in response to pathogen volatile metabolites may have progeny better equipped to survive pathogen exposure during their lifetime. To test this hypothesis, we exposed hermaphrodite mothers (P0 generation) to the volatile metabolites of *P. aeruginosa* from the L4 stage until adulthood day 2. After 48 hours of exposure, we isolated the offspring (F1 generation) and cultured them on plates seeded with *E. coli* until they reached the L4 stage. Subsequently, we transferred these animals to plates seeded with *P. aeruginosa* and monitored their survival. Offspring from hermaphrodite mothers exposed to *E. coli* scent served as the control group. As shown in **Supplementary Fig. 2**, the survival of F1 animals does not significantly differ from the control group; however, a slight upward trend is observed. To investigate this further, we conducted a more detailed analysis by examining the data for each biological replicate individually. We observed that F1 animals exhibited increased survival when their mothers originated from populations (biological replicates) with a higher average number of exophers and stronger responses to PA14 scent. Consequently, we categorized our data into two groups based on two criteria: (i) populations with more or fewer than 7 exophers on average in the P0 generation, and (ii) populations where P0 worms exposed to PA14 produced more or fewer than 10 exophers. As illustrated in **Fig. 8e**, F1 animals from the high exopher-producing group exhibited significantly longer survival following infection (while P0 animals lived significantly shorter lives) compared to control F1 animals. In contrast, there was no statistically significant difference in survival between the low exopher-producing group and the control group for either the P0 or F1 generations (**Fig. 8f**). These findings suggest that when hermaphrodite mothers produce a large number of exophers in response to pathogen-derived volatile metabolites, their offspring exhibit enhanced survival, albeit at the cost of maternal survival.

**Model of exopher regulation mechanism in *C. elegans***
Based on our investigations, we propose the following model outlining the complex mechanism of exopher regulation by pathogen-derived metabolites (Fig. 9):

1. Pathogen-induced exopher production: Exposure to live *Pseudomonas aeruginosa* PA14 or *Serratia marcescens* Db10 induces exopher production in *C. elegans* body wall muscles.

2. Immune pathway involvement: The production of exophers is influenced by key immune pathways (insulin, TGFβ, p38 MAPK, and IPR), although pathogen-induced exophergenesis occurs in most immune mutants.

3. Non-volatile and volatile pathogen metabolites: Both non-volatile (supernatant) and volatile pathogen metabolites trigger exopher production, with distinct sensory neurons (ADL, ASK, AWC) involved in regulation. Neurons such as ASI, ASH, and AWB regulate non-volatile metabolite-induced exopher production but not volatile metabolite-induced production.

4. Involvement of GPCRs: Neuronally-expresssed and non neuronally-expressed GPCRs *sri-36*, *sri-39*, *sri-19*, and *srr-6* play key roles in inducing exophergenesis upon exposure to pathogen non-volatile metabolites.

5. Offspring survival and maternal cost: Offspring of mothers producing many exophers in response to pathogen metabolites exhibit increased survival during infection, while the mothers themselves experience reduced survival, indicating a trade-off between maternal survival and offspring fitness.

## Discussion

Our findings suggest that, although exophers produced in response to different stimuli may appear similar in number, the distinct signalling pathways involved indicate potential differences in their roles or contents. Specifically, supernatant-induced exopher production, which depends on immune pathways such as p38 MAPK and TGF-β, differs from volatile-
316 induced exopher production, which appears to operate independently of these pathways. This 317 distinction implies that exophers may constitute distinct subtypes of EVs with unique molecular 318 compositions and functions. The possibility that quantitatively similar exophers could be 319 functionally distinct opens new research avenues to isolate and characterize these vesicles in 320 detail. By analysing their content in response to both volatile and non-volatile metabolites, we 321 could uncover their specific roles in organismal health and pathogen defence. Our results further 322 reveal that the mechanisms triggering exopher production are influenced by the type of 323 metabolite detected: non-volatile pathogen metabolites, signalling a more immediate threat, 324 activate immune pathways to induce exopher production, while volatile metabolites, which 325 suggest the pathogen is nearby but not directly infecting, bypass these immune pathways. This 326 discrepancy underscores the complexity of the worm's physiological responses to 327 environmental cues, suggesting that exopher production is finely regulated based on the nature 328 of the perceived threat. Consequently, non-volatile metabolite-induced exophers may play a 329 more immediate role in worms physiology, while volatile-induced exophers could serve to 330 prepare the organism for future stressors.

331 Previous studies have shown that increased exopher release can benefit the organism by 332 removing protein aggregates¹³, extending lifespan¹⁶, or promoting faster offspring 333 development¹⁴. However, when exopher release is elevated in response to pathogen exposure, 334 we observe an opposite effect, leading to decreased survival upon infection. This suggests that 335 exophers, or possibly EV in general, may function under a hormetic response: while a moderate 336 increase in EV production appears beneficial, an excessive increase may overwhelm the 337 organism, negating any positive effects. Thus, while moderate exopher production may be 338 beneficial, too much exopher release might impose a burden on the organism, potentially due 339 to changes in the content of these vesicles under different environmental conditions.
Interestingly, while volatile metabolites like 1-undecene have been shown to increase lifespan in *C. elegans* under non-pathogenic conditions⁴⁶ or to protect worms against a subsequent infection with *P. aeruginosa*³¹, our results demonstrate that volatile-induced exopher production can lead to decreased survival during infection. The differences in the type, timing, and context of exposure likely contribute to this contradiction. In previous studies, a specific compound and shorter exposure periods were used. In contrast, our study involved prolonged exposure to a mixture of volatile metabolites from pathogens, which may trigger different physiological responses. The involvement of multiple G protein-coupled receptors (GPCRs) in regulating exopher production suggests that exophergenesis is not triggered by a single metabolite but by a complex cocktail of pathogen-derived signals. This complexity may allow the organism to fine-tune its response depending on the nature of the threat it perceives, enabling a more nuanced and context-dependent reaction to environmental challenges.

In conclusion, our study highlights the complexity of exopher production in response to pathogen-derived signals. The ability of *C. elegans* to detect and respond to volatile and non-volatile metabolites in a context-dependent manner suggests that exophers and other EVs play a crucial role in mediating the organism's physiological response to environmental stressors. Future research should focus on isolating and characterizing exophers produced under different conditions to determine their specific molecular contents and functions. Understanding how these vesicles contribute to both the short-term survival of the organism and the long-term fitness of its offspring will provide deeper insights into the adaptive roles of EVs in host-pathogen interactions as well as in animals healthspan and lifespan.

361
362 **Methods**

363 **Worm Maintenance and Strains**

364 *C. elegans* strains were maintained at 20°C on nematode growth medium (NGM) plates seeded with *Escherichia coli* OP50 as a food source⁴⁷. Only hermaphrodites were used in the experiments. A comprehensive list of all chemicals and strains used in the study are provided in Supplementary Table 1 and 2, respectively.

368 **Pathogen procedures**

369 **Pathogen bacteria media plates preparation**

370 Worms were exposed to either *Pseudomonas aeruginosa* PA14 or *Serratia marcescens* Db10 strains. Pathogen-seeded plates were prepared following standard protocols⁴⁸,⁴⁹.

371 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.

372 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.

378 All the experiments with the pathogenic bacteria were conducted in Biosafety level 2 laboratory.
385 **Short time infection assay**

386 Worms were age-synchronized by isolating pretzel-stage embryos. Upon reaching the first day
387 of adulthood (AD1), they were transferred either to control plates seeded with *E. coli* OP50 or
388 to plates seeded with the pathogens PA14 or Db10. Worms were exposed directly to the
389 pathogens for 3 hours at 20°C, after which they were transferred back to OP50 seeded plates.
390 Exopher levels were assessed the following day, on the second day of adulthood (AD2).

391 **Pathogen supernatant assay**

392 To collect non-volatile metabolites, a single colony of PA14 was inoculated into 5 mL of LB
393 media and cultured overnight for a maximum of 16 hours at 37°C. After incubation, bacterial
394 cells were removed by passing the culture through a 0.22 µm filter, and the bacterial supernatant
395 was collected. Age-synchronized L4 stage worms (n = 30), grown on 60 mm NGM plates
396 seeded with OP50, were treated with 50 µL of the filtered bacterial supernatant, while control
397 worms received 50 µL of LB broth. Plates were sealed with parafilm, and exophers were scored
398 48 hours later, when the worms reached AD2.

399 **Volatile metabolites chamber assay**

400 Pretzel-stage embryos were placed on 35-mm NGM plates seeded with *E. coli* OP50, with 10
401 embryos per plate. Once the embryos developed into L4 stage worms, a chamber with volatile
402 metabolites was assembled by placing a 35 mm SK plate containing PA14 or a control 35 mm
403 NGM plate with OP50 on the bottom. The plate with synchronized worms was positioned on
404 top, and the two plates were sealed together with parafilm. Worms were incubated with volatile
405 metabolites of the bacteria for 48h hours. Exophers were evaluated at the second day of
406 adulthood.
407 **Offspring survival assay**

408 The parental generation (P0 generation) of *C. elegans* was synchronized by placing 10 pretzel-
409 stage embryos on 35 mm NGM plates seeded with OP50. As described in the “Volatile
410 Metabolites Chamber Assay,” chambers were assembled using either OP50 or PA14 when the
411 worms reached the L4 stage. After 48 hours of exposure to volatile metabolites, exophers were
412 scored in the parental generation on the AD2.

413 Next, pretzel-stage embryos (F1 generation) of the P0 exposed to OP50 or PA14 volatiles were
414 collected and placed on 35 mm NGM plates seeded with OP50 (15 embryos per plate). When
415 the F1 worms reached the L4 stage, they were infected according to the standard infection assay
416 (references). L4 larvae were transferred to SK plates and incubated at 25°C. FUdR was not
417 included in the plates.

418 The survival of the F1 population was monitored at multiple time points using a touch
419 movement assay. Worms that failed to respond to touch were scored as dead, removed from the
420 killing plates, and recorded. Worms that responded to touch were scored as alive and also
421 counted. Survival was recorded at least twice daily until the entire population had died.

422 **Egg retention assay**

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

428 RNA Interference Assay

429 RNA interference (RNAi) in *C. elegans* was performed using the standard RNAi feeding
430 method⁵⁰. Briefly, RNAi plates were prepared by supplementing NGM with 12.5 µg/mL
431 tetracycline, 100 µg/mL ampicillin, and 1 mM IPTG. These plates were seeded with *E. coli*

432 HT115 bacteria expressing double-stranded RNA (dsRNA) targeting the gene of interest.

433 Control worms were fed *E. coli* HT115 containing the empty vector L4440.

434 Age-synchronized pretzel-stage embryos were transferred onto the freshly prepared RNAi

435 plates and cultured until day 2 of adulthood, at which point exophers were quantified. The

436 developmental stage of the worms was confirmed at the L4 stage, and any individuals that were

437 developmentally advanced or delayed were excluded from the experiment.

438 Transcriptome analysis

439 *C. elegans* RNA extractions, library preparations, and sequencing were performed by Azenta

440 US, Inc (South Plainfield, NJ, USA) as follows:

441 RNA extraction

442 Total RNA was extracted using Qiagen RNeasy Plus mini kit (Qiagen, Hilden, Germany)

443 following the manufacturer's instructions.

444 Library preparation with polyA selection and Illumina sequencing

445 RNA samples were quantified using the Qubit 2.0 Fluorometer (Life Technologies, Carlsbad,

446 CA, USA), and their integrity was assessed with the Agilent TapeStation 4200 (Agilent

447 Technologies, Palo Alto, CA, USA). RNA sequencing libraries were constructed using the

448 NEBNext Ultra II RNA Library Prep Kit for Illumina, following the manufacturer's protocol

449 (NEB, Ipswich, MA, USA). In brief, mRNA was enriched using Oligo(dT) beads and

450 subsequently fragmented at 94°C for 15 minutes. First and second-strand cDNA synthesis was

451 performed, followed by end repair and adenylation of the cDNA fragments at their 3' ends.

452 Universal adapters were then ligated to the cDNA fragments, and libraries were enriched

453 through a limited-cycle PCR with the addition of indexing sequences. The resulting sequencing
454 libraries were validated using the Agilent TapeStation and quantified with both the Qubit 2.0
455 Fluorometer (Invitrogen, Carlsbad, CA, USA) and quantitative PCR (KAPA Biosystems,
456 Wilmington, MA, USA). The libraries were multiplexed and loaded onto the Illumina NovaSeq
457 6000 platform according to the manufacturer's instructions. Sequencing was performed with a
458 2×150 paired-end (PE) configuration using v1.5 reagents. Image analysis and base calling were
459 carried out using the NovaSeq Control Software v1.7. The raw sequence data (.bcl files)
460 generated were converted into fastq files and de-multiplexed using the Illumina bcl2fastq
461 software (version 2.20), allowing for one mismatch in index sequence identification.

462 *Sequencing data analysis*

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

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

477 Exopher quantification was performed as described in Turek et al.¹⁴ and Banasiak et al.²⁰ (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 pretzel-stage embryos 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 recorded.

483 Representative fluorescence images were captured using a Zeiss LSM800 laser-scanning confocal microscope equipped with a 40× oil immersion objective. GFP and RFP fluorescence were excited using 488 nm and 561 nm lasers, respectively. For imaging, worms were immobilized on 5% agarose pads, using either 10 µl of PolySciences 0.05 µm polystyrene microspheres or 25 µM tetramisole as an anesthetic.

488 **Generation of *sri-19*, *sri-36/39*, and *srr-6* mutant strains**

489 CRISPR/Cas9 genome editing was employed to generate the *sri-19* mutants (*sri-19(wwa15)* and *sri-19(wwa16)*) following previously established protocols⁵¹. The crRNA sequence used to target the *sri-19* locus was ATAATTGGTGGATATACAAATGG. Mutations were mapped to the first exon, resulting in frame shifts that likely produce molecular null alleles.

493 To create *srr-6* mutants, a previously described STOP-IN strategy⁵² 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
494
495
496 GGGAAGTTTGTCCAGAGCAGAGGTGACTAAGTGATAA, flanked by
497 AATCTTTTTCAACAATGATTACTCCAAGTCCTGAAGTCGT (left) and
498 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.

## 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 Figures 2, 3, 4, 5, 7, and 8. Given the assumption of non-Gaussian distribution of residuals, nonparametric statistical tests were employed. For pairwise comparisons, two-tailed Mann-Whitney tests were used, while Kruskal-Wallis tests followed by Dunn's multiple comparisons test were applied for multi-group comparisons. A p-value of < 0.05 was considered statistically significant.

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644 Acknowledgements

645 Some strains were provided by the CGC, which is funded by NIH Office of Research

646 Infrastructure Programs (P40 OD010440). We thank Monika Woźniak, Natalia Wasiak,
Małgorzata Śledź, Tomasz Strumiński for assistance with worms maintenance; Adam Kłosin for discussions and comments on the manuscript. Work in the MT Laboratory was mainly funded by a National Science Centre SONATA grant (2019/35/D/NZ3/04091 to MT) and additionally supported by a National Science Centre SONATA BIS grant (2021/42/E/NZ3/00358 to MT). Work in the WP Laboratory was funded by the Norwegian Financial Mechanism 2014-2021 operated by the Polish National Science Centre, Poland (project contract number 2019/34/H/NZ3/00691 to WP).

654

655 Author Contributions

Conceptualization: MT; Data curation: MT; Formal analysis: KK, AS, MT, WP, NP; Funding acquisition: MT, WP, NP; Investigation: KK, AS, MT; Methodology: MT, NP, WP, KK, AS; Project administration: MT; Resources: MT, NP, WP; Supervision: MT, NP; Validation: MT, WP, KK, AS, NP; Visualization: KK, AS, MT; Writing – original draft: MT; Writing – review & editing: MT, WP, KK, AS, NP.

661

662 Competing Interests

The authors declare no competing interests.
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>
666 **Figure 1.** Production of *C. elegans* muscle exophers is upregulated during pathogen infection.
667

668 a Experimental Setup: Synchronized AD1 worms were exposed to *Pseudomonas aeruginosa* (PA14) and *Serratia marcescens* (Db10), or to *Escherichia coli* (OP50) for 3 hours
669 at 20°C, followed by transfer to OP50-seeded plates. Exopher production was assessed on the
670 second day of adulthood (AD2). Created with BioRender.com.
671

672 b Short time infection with *P. aeruginosa* PA14 or *S. marcescens* Db10 leads to increased
673 exopher production (n = 60 worms, N = 2 independent experiments).
674

675 c Investigated innate immunity pathways: Various innate immunity pathways were
676 assessed for their roles in regulating exopher production.
677

678 d Worms deficient in key immune response pathways exhibited changes in exopher levels
679 (n = 90 worms, N = 3 independent experiments; n = 90-180 worms, N = 3-6 independent
680 experiments).
681

682 e - g Infection-induced exopher production is not dependent on the (e) insulin signalling, (f) p38 MAPK, or (g) TGF-β pathways pathway (n = 37-60 worms, N = 2 independent experiments). The data shown in graphs e-h were collected together and share the same controls but are presented in separate panels to improve visualization and enhance clarity.
683

684 h Exopher production in response to *S. marcescens* Db10 infection is fully dependent on
685 the IPR pathway, while production in response to *P. aeruginosa* PA14 infection is partially
686 dependent on this pathway (n = 51-58 worms, N = 2 independent experiments). The data shown
687 in graphs e-h were collected together and share the same controls but are presented in separate
688 panels to improve visualization and enhance clarity.
689

689 i Exposure to *S. marcescens* Db10, but not *P. aeruginosa* PA14, results in embryo
689 retention in the uterus (n = 54-75 worms, N = 3-4 independent experiments).
690 Data are presented as medians with interquartile ranges. Non-significant p-values (p > 0.05) are

691 highlighted in pink, while significant p-values (p < 0.05) are shown in blue. Statistical

692 significance was assessed using the Kruskal-Wallis test with Dunn's multiple comparisons test.

693
a

<figure><img src="image_11.png" /></figure>

b

<figure><img src="image_12.png" /></figure>

c

<figure><img src="image_13.png" /></figure>

d

<figure><img src="image_14.png" /></figure>

e

<figure><img src="image_15.png" /></figure>

f

<figure><img src="image_16.png" /><figcaption>Figure 2. The production of muscle exophers in *C. elegans* is regulated by both volatile and non-volatile metabolites from pathogens.</figcaption></figure>

a Experimental setup schematic: Synchronized L4-stage worms were exposed to PA14 volatile metabolites or OP50 for 48 hours, and exopher production was evaluated on the second day of adulthood (AD2). Created with BioRender.com.

b Exposure to PA14 volatile metabolites significantly increases exopher levels in worms (n = 77-90 worms, N = 3 independent experiments).

c Volatile metabolites exposure causes embryo retention in the uterus (n = 90 worms, N = 3 independent experiments).
704 d Experimental setup schematic: L4-stage worms were exposed to 50 µL of filtered
705 pathogen supernatant, while controls received 50 µL of LB broth. Exophers were scored after
706 48 hours, at AD2.

707 e Exposure to PA14 supernatant results in increased exopher production (n = 90 worms,
708 N = 3 independent experiments).

709 f PA14 supernatant exposure does not induce embryo retention (n = 67-70 worms, N = 3
710 independent experiments).

711 Data are presented as medians with interquartile ranges. Statistical analyses were performed
712 using the two-tailed Mann-Whitney test, with non-significant p-values (p > 0.05) in pink and
713 significant p-values (p < 0.05) in blue.

714
a

PA14 volatile metabolites ::::

<figure><img src="image_17.png" /></figure>

b

PA14 non-volatile metabolites ⌜

<figure><img src="image_18.png" /></figure>

c

<table><thead><tr><th></th><th>genes of the pathway</th><th>PA14 volatile metabolites</th><th>PA14 supernatant</th></tr></thead><tbody><tr><td rowspan="2">p38 MAPK</td><td>tir-1</td><td>p &lt; 0.0001</td><td>p = 0.4776</td></tr><tr><td>pmk-1</td><td>p &lt; 0.0001</td><td>p = 0.0503</td></tr><tr><td rowspan="2">Insulin Signaling</td><td>akt-1</td><td>p = 0.0059</td><td>p = 0.0203</td></tr><tr><td>daf-16</td><td>p &lt; 0.0001</td><td>p = 0.0174</td></tr><tr><td>TGF-β</td><td>dbl-1</td><td>p &lt; 0.0001</td><td>p = 0.5061</td></tr><tr><td>IPR</td><td>cul-6</td><td>p = 0.0007</td><td>p = 0.4151</td></tr></tbody></table>
717 **Figure 3. Exopher production in response to pathogen volatile metabolites and**
718 supernatant is governed by distinct regulatory mechanisms.

719 a Increased exopher production after exposure to PA14 volatile metabolites does not
720 depend on innate immunity pathways (n = 80-90 worms, N = 3 independent experiments).

721 b Increased exopher production after exposure to PA14 non-volatile metabolites depends
722 on p38, TGF-β, and IPR pathways (n = 85-120 worms, N = 3-4 independent experiments).

723 c Summary of experimental results: A table summarizing the experimental findings,
724 including p-values. Created with BioRender.com.

725 Data are presented as medians with interquartile ranges. Statistical analyses were performed
726 using the two-tailed Mann-Whitney test, with non-significant p-values (p > 0.05) in pink and
727 significant p-values (p < 0.05) in blue.

728
a

PA14 volatile metabolites !!!

<figure><img src="image_19.png" /></figure>

b

PA14 non-volatile metabolites ◊

<figure><img src="image_20.png" /></figure>

c

<table><thead><tr><th></th><th>PA14 volatile<br>metabolites</th><th>PA14<br>supernatant</th></tr></thead><tbody><tr><td>ASK(-)</td><td>p = 0.9039</td><td>p = 0.3163</td></tr><tr><td>ADL(-)</td><td>p = 0.5055</td><td>p = 0.5272</td></tr><tr><td>ASI(-)</td><td>p < 0.0001</td><td>p = 0.1678</td></tr><tr><td>AQR/PQR/<br>URX(-)</td><td>p = 0.0004</td><td>p = 0.0095</td></tr><tr><td>AWC(-)</td><td>p = 0.3608</td><td>p = 0.1583</td></tr><tr><td>AWB(-)</td><td>p = 0.0014</td><td>p = 0.4886</td></tr><tr><td>ASH(-)</td><td>p < 0.0001</td><td>p = 0.1579</td></tr></tbody></table>
731 **Figure 4.** Chemosensory neurons regulate exopher production in response to pathogen
732 **metabolite exposure.**

733 a Exopher production upon exposure to PA14 volatile metabolites is dependent on ASK,
734 ADL, and AWC neurons (n = 80-110 worms, N = 3-4 independent experiments). The data are
735 presented in three separate graphs because three different exopher reporter lines, each
736 exhibiting varying levels of basal exopher production, were used. The usage of different
737 exopher reporter lines was due to crossing incompatibilities with specific neuronal ablation
738 mutants.

739 b Regulation of exopher production upon PA14 supernatant exposure involves multiple
740 neurons, including ASK, ADL, ASI, AWB, AWC, and ASH (n = 90-120 worms, N = 3-4
741 independent experiments). The data are presented in three separate graphs because three
742 different exopher reporter lines, each exhibiting varying levels of basal exopher production,
743 were used. The usage of different exopher reporter lines was due to crossing incompatibilities
744 with specific neuronal ablation mutants.

745 c Summary of experimental results: A table summarizing the experimental findings,
746 including p-values. Created with BioRender.com.

747
a

<figure><img src="image_21.png" /></figure>

b

<figure><img src="image_22.png" /></figure>

c

<figure><img src="image_23.png" /></figure>

d

<table><thead><tr><th></th><th>PA14 volatile<br>metabolites</th><th>PA14<br>supernatant</th></tr></thead><tbody><tr><td>AIB(-)</td><td>p = 0.1078</td><td>p = 0.1162</td></tr><tr><td>npr-9</td><td>p = 0.7391</td><td>p = 0.5374</td></tr></tbody></table>

748

749 **Figure 5.** AIB interneuron and NPR-9 receptor integrate sensory responses to mediate exopher production.

750

751 a Exopher production in strains lacking the AIB interneuron or NPR-9 receptor is comparable to that in wild-type worms (n = 90 worms, N = 3 independent experiments).

752

753 b - c AIB interneuron and AIB-specific NPR-9 receptor are required for exopher production triggered by pathogen (b) volatile and (c) non-volatile metabolites (n = 88-91 worms, N = 3 independent experiments).

754

755

756 d Summary of experimental results: A table summarizing the experimental findings, including p-values. Created with BioRender.com.

757

758
<figure><img src="image_24.png" /><figcaption>**Figure 6.** Comparative transcriptomic analysis of worms producing many and few exophers per individual.</figcaption></figure>

a Principal component analysis (PCA) comparing worms with high exopher production (>20 exophers) and low exopher production (<2 exophers).

b Volcano plot showing differential gene expression between worms producing many exophers (>20 exophers) and few exophers (<2 exophers).

c Table listing 7TM GPCR transcripts with significant changes in expression levels.

d Gene Ontology (GO) term analysis plot based on the transcriptome results.
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770 **Figure 7. Exopher production induced by PA14 non-volatile metabolites is regulated by**
771 **multiple GPCRs.**

772 a Exopher production in worms lacking the SRI-19 receptor is comparable to that in wild-
773 type worms (n = 90-180, N = 3-6 independent experiments).

774 b Increased exopher production after exposure to PA14 volatile metabolites does not
775 depend on SRI-19 receptor (n = 90-180, N = 3-6 independent experiments).

776 c The SRI-19 receptor is required for exopher production induced by PA14 non-volatile
777 metabolites (n = 90-180, N = 3-6 independent experiments).

778 d The *sri-19* gene encoding 7TM receptor is expressed in ADL neurons, based on position
779 and scRNAseq data<sup>53</sup>, consistent with observations in at least 20 animals from three replicates.

780 e Exopher production in worms lacking the SRI-36 and SRI-39 receptors is comparable
781 to that in wild-type worms (n = 90, N = 3 independent experiments).

782 f Increased exopher production after exposure to PA14 volatile metabolites does not
783 depend on SRI-36 and SRI-39 receptors (n = 90, N = 3 independent experiments).

784 g The SRI-36 and SRI-39 receptors are required for exopher production induced by PA14
785 non-volatile metabolites (n = 90-120, N = 3-4 independent experiments).

786 h The *sri-36* and *sri-39* genes encoding 7TM receptors are expressed in neurons
787 (including ASK# and ASI#) and the alimentary tract (red arrow – pharynx, green arrow –
788 intestine), consistent with observations in at least 20 animals from three replicates. #based on
789 position and Vidal et al.<sup>43</sup>.

790 i Basal exopher levels in *srr-6* mutants is increased compared to wild-type worms (n =
791 90-180, N = 3-6 independent experiments).

792 j Increased exopher production after exposure to PA14 volatile metabolites does not
793 depend on SRR-6 receptor (n = 90-180, N = 3-6 independent experiments).
794 k The SRR-6 receptor is required for exopher production induced by PA14 non-volatile
795 metabolites (n = 90-180, N = 3-6 independent experiments).

796 l The srr-6 gene encoding 7TM receptor is expressed in neurons of the retrovesicular
797 ganglion (encircled), pharynx neurons (black arrow), alimentary tract (green arrow – intestine),
798 and excretory system (white arrow), consistent with observations in at least 20 animals from
799 three replicates.

800 Data are presented as median with interquartile range; not significant p values (p > 0.05) are in
801 pink colour, significant p values (p < 0.05) are in blue colour; Kruskal-Wallis test with Dunn's
802 multiple comparisons test (a, e, i) two-tailed Mann-Whitney test (b, c, f, g, j, k). Scale bars are
803 20 µm.
<figure><img src="image_37.png" /><figcaption>F1 generation</figcaption></figure>

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805 **Figure 8. Exophers levels are affecting survival rate post-infection.**

806 a Experimental setup schematic: Age-synchronized L4-stage worms were exposed to PA14 volatile metabolites for 48 hours. After this exposure, exopher production was quantified at the AD2 stage, and embryos from the F1 generation were collected. The P0 worms were subsequently transferred to Slow Killing (SK) plates seeded with PA14, where their survival was monitored. Once the F1 worms reached the L4 stage, they were subjected to a PA14 infection assay to assess their survival. Created with BioRender.com.
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808
809
810
811

812 b Wild-type worms exposed prior to infection to pathogen-derived volatile metabolites exhibited reduced survival compared to the control group. In contrast, worms with ablated ASK neurons, which produce low number of exophers, showed significantly improved survival, regardless of prior exposure to volatile metabolites (n = 53-90 worms, N = 3-5 independent experiments).
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814
815
816

817 c Worms with *rme-2* gene knockdown, which produce low number of exophers, demonstrated enhanced survival rates upon PA14 infection (n = 68-75 worms, N = 4 independent experiments).
818
819

820 d The SRI-19 receptor that regulate exopher production upon exposure to PA14 non-volatile metabolites also regulates survival in response to PA14 infection (n = 102-108 worms, N = 4 independent experiments).
821
822

823 e F1 animals from the high exopher-producing group showed significantly longer survival after infection compared to control F1 animals, although the P0 animals had significantly shorter lifespans (n = 53-87 worms, N = 3 independent experiments).
824
825

826 f In contrast, there was no statistically significant difference in survival between the low exopher-producing group and the control group for either the P0 or F1 generations (n = 83-183 worms, N = 4-6 independent experiments).
827
828
829 Graphs (b-f) are plotted as Kaplan-Meier survival curves, not significant p values (p > 0.05) are

830 in pink color, significant p values (p < 0.05) are in blue color.

831
<figure><img src="image_46.png" /><figcaption>Figure 9. Model of exopher regulation from muscles by pathogen non-volatile and volatile metabolites.</figcaption></figure>

832

833

834

835
a

sri-19(wwa14)

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sri-19(wwa16)

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c

sri-36/-39(wwa57)

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sri-36/-39(wwa58)

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b

srr-6(wwa48)

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srr-6(wwa49)

<figure><img src="image_52.png" /><figcaption>Supplementary Figure 1. Diagrams of (a) sri-19, (b) srr-6, (c) sri-36, and sri-39 genomic structures and genetic lesions (marked in pink) used in the study (related to Materials and Methods).</figcaption></figure>

836
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838
839
840
<figure><img src="image_53.png" /><figcaption>Supplementary Figure 2. Exophergenesis levels influence post-infection survival rates.</figcaption></figure>

a-c Summarized data from Fig. 8e and 8f show that (a) basal exopher production did not exceed a median of 6 exophers per animal in the control group and 10 exophers per animal in the exposed group. (b) No statistically significant beneficial effect on offspring survival was observed following P0 exposure to PA14 volatile metabolites. While the P0 generation exposed to PA14 volatile metabolites showed reduced survival after infection (n = 123-233 worms, N = 6-8 independent experiments).

Graphs (b-c) are plotted as Kaplan-Meier survival curves, not significant p values (p > 0.05) are in pink colour, significant p values (p < 0.05) are in blue colour.