Bacterial extracellular vesicles as recyclable nutrient reservoirs

Domain: chemistry
Published: 2026-04-06
Editorial outcome: minor_revision

Abstract
Bacterial extracellular vesicles (EVs) are known to mediate intercellular communication, virulence, and immune modulation. Here we show that bacteria can utilise EVs also as recyclable nutrient reservoirs. Using Bacillus cereus as a model organism, we demonstrate that EVs exhibit distinct dynamics depending on growth conditions: EVs produced in complex nutrient-rich media undergo time-dependent degradation, while those produced in defined nutrient-limited conditions remain stable and accumulate. We observe similar EV degradation patterns in Staphylococcus aureus. Time-resolved multi-omics profiling reveals that EVs containing the lipid sphingomyelin undergo progressive degradation. Using pharmacological inhibition, knockout mutants, and enzymatic complementation, we show that this process is driven by secreted sphingomyelinase (SMase). This enzyme contributes to degradation of sphingomyelin-containing EVs, thereby releasing their biomolecular cargo which can be used as a nutrient source. Growth assays confirm that SMase-mediated EV degradation provides a growth advantage when nutrients become depleted, thus establishing EVs as dynamic nutrient reservoirs.

Introduction
Adaption to environmental conditions is a prerequisite for the persistence and survival of bacterial populations. Multiple mechanisms and diverse lifecycle styles, including spore formation1 and post-mortem nutrient acquisition2, are employed by bacterial cells to adapt to specific niches and overcome challenges posed by adverse environmental conditions. Here, we report on a yet-to-explore strategy for bacterial adaption: extracellular vesicles (EVs). EVs, which are found in all three kingdoms of life3, are lipid bilayer-enclosed spheres composed of the biomolecular building blocks lipids, proteins and nucleic acids4. While lipids are the major structural component defining EV morphology, proteins and nucleic acids are attached to or contained within EVs5. Over the last decade, EVs have gained increasing prominence as vehicles for RNA therapeutics6, as vaccine platforms7, as biomarkers for cancer8 and infections9–11.

Although bacterial EVs are thought to be involved in various biological processes, research has mainly focused on their role in pathogenicity12,13. For instance, we have recently demonstrated that EVs of the Gram-positive human pathogen Bacillus cereus are biologically active and facilitate shuttling of tripartite toxins to host cells in a protected manner, where they elicit inflammatory responses14. As mediators of virulence, EVs can also participate in biofilm formation15, contribute to antibiotic resistance16, and inhibit growth of other competing bacterial species17. Although progress has been made in understanding the functions of bacterial EVs, the role of the bacterial EV lipid bilayer remains poorly understood. For instance, sphingolipids are repeatedly reported as major constituents of bacterial EV lipid bilayers18–21. Yet, the majority of bacterial species, including B. cereus, are unable to synthesise sphingolipids de novo22,23. Nevertheless, they may be capable of scavenging sphingolipids from their environment24. Despite consensus on the presence of sphingolipids in bacterial EVs, their functional role within bacterial EV membranes remains to be elucidated.

Contrary to the prevailing concept of EVs accumulating over time in the extracellular space of bacteria, here we demonstrate that EVs derived from bacterial cultures grown in complex nutrient-rich LB-Miller (LB) medium or host factor-enriched RPMI (hfRPMI) medium undergo degradation. Notably, EVs from bacterial cultures grown under nutrient-limited conditions (MOD and RPMI medium) do not degrade but accumulate over time, indicating distinct functionalities of bacterial EVs tightly linked to environmental factors. We exclude inherent instability, biophysical features, or adjacent cells as the cause of the particular dynamics and behaviour of these EVs. Using a multi-omics approach and complementary functional studies, we demonstrate that EV degradation requires two key factors: sphingolipid-rich EV architecture and the presence of sphingomyelinase (SMase). Our work reveals that SMase-mediated EV-degradation is integral for bacterial adaption. In response to starvation, only SMase-targetable EVs consisting of sphingomyelins can serve as nutrient reservoirs. This physiologically relevant interaction between SMase and the EV lipid architecture could support bacterial adaption to distinct environments. Given the conservation of SMase and the structural similarity between bacterial and eukaryotic lipids, deciphering these enzyme-EV interactions will redefine the boundaries of EV biology.

Results
EV secretion dynamics in complex nutrient-rich and defined nutrient-scarce environments
To investigate how nutrient complexity affects EV secretion in Gram-positive bacteria, we compared B. cereus EV yields from complex, nutrient-rich (LB) and defined, nutrient-scarce (MOD) media over time. The emetic B. cereus reference strain F4810/72, which served as a model organism, was grown either in LB or in MOD. EVs were isolated from bacterial cultures after 0 h, 3 h, 6 h, 9 h, 12 h and 15 h by differential centrifugation followed by ultracentrifugation, as outlined in figure 1a (Fig. 1a). The EVs isolated from B. cereus cultures were designated as EVsLB or EVsMOD, respectively. Immediately after inoculating LB and MOD with B. cereus, as well as in sterile media controls, no EVs were detectable (Fig. 1b). However, a marked increase in B. cereus EV yields occurred during the initial 6 h of cultivation. Specifically, a 70-fold increase in EV yields was observed between 3 h and 6 h in both LB and MOD, resulting in comparable EV yields of EVsLB and EVsMOD at 6 h. Unexpectedly, EV yields decreased significantly after 9 h in LB but remained stable in MOD (Fig. 1b). This decrease might either reflect a different stability of EVsLB and EVsMOD or might be linked to distinctive factors actively degrading EVsLB.

Biophysical properties of EVs or bacterial presence do not drive EV degradation
To test whether the observed differences in the dynamics of bacterial EV decrease relate to distinctive biophysical characteristics, we assessed biophysical properties of EVs using atomic force microscopy (AFM, Fig. 1c - f, Supplementary Fig. 1a-f). In addition, we employed two complementary transmission electron microscopy (TEM) approaches: (i) imaging of ultrathin sections prepared from resin-embedded B. cereus EVs that were subsequently stained (Supplementary Fig. 2a, b), and (ii) the drop-on-grid method, in which B. cereus EVs were directly dropped onto TEM grids (Supplementary Fig. 2c, d). The TEM analyses confirmed that B. cereus EVs deriving from both media are lipid-bilayer bordered entities that are sphere-shaped. In the sterile media (LB, MOD) controls, no particle-like structures were detected by TEM (Supplementary Fig. 2e, f). Nanoparticle tracking analysis (NTA; Supplementary Fig. 2g) was used to assess the size of EVs. EVsLB (NTA: 195.3 nm) were found to be larger than EVsMOD (NTA: 142.3 nm), resulting in a size difference of 53.0 nm, which was validated by isolating EVs from three additional pathogenic B. cereus strains (Supplementary Fig. 2g). EVsLB and EVsMOD showed similar stability in AFM analysis, consistent with the observation that EVs remain intact when spiking them into sterile LB or MOD medium (Fig. 1g). These results highlight the inherent stability of both EVsLB and EVsMOD, suggesting that other factors mediate the degradation of EVsLB.

To decipher the role of direct contact with adjacent bacteria in EV degradation, bacteria were cultivated for 7 h (t0) in the respective media. Thereafter, bacterial cells were removed to produce cell-free conditioned media. The decrease in EV numbers in cell-free conditioned medium was determined after 4.5 h. As expected, no significant reduction of endogenous EVsMOD was observed. In contrast, endogenous EVsLB were found to be degraded in cell-free conditioned medium (Fig. 1h), indicating that bacterial contact is not required for EV degradation.

EV degradation in host-factor-enriched RPMI parallels results from complex lab cultivation medium
Next, we asked whether EV degradation in LB and EV stability in MOD are specific phenomena in these particular growth environments or if they represent a more general feature of bacterial EVs associated with distinct environments. To answer this question, we compared the dynamics of EV production and degradation in two additional environments: host-factor-enriched RPMI medium and unconditioned RPMI medium (Supplementary Fig. 3a). To produce host-factor-enriched RPMI, Caco-2 cells were first differentiated in RPMI medium. Subsequently, the supernatant of the Caco-2 cells was collected by centrifugation, and host EVs were depleted by ultracentrifugation. This RPMI medium enriched with host factors and depleted of host EVs is designated as hfRPMI. The number of B. cereus EVs was monitored in bacterial cultures grown in parallel in hfRPMI and unconditioned RPMI. In concordance with the results from experiments in LB and MOD, a significant decrease in bacterial EVs was observed after 4.5 h of cultivation in hfRPMI, but no change in bacterial EV counts was observed in RPMI (Supplementary Fig. 3a, b). These findings imply that EV degradation and EV stability are not specific to LB and MOD but rather appear to be linked to the complexity of the environmental nutrient composition.

EV degradation is not species-specific but a more common trait in bacteria
To test whether EV degradation is specific for B. cereus EVs, or whether it also occurs in other bacteria, Staphylococcus aureus Newman was cultured in different growth media (LB, hfRPMI, MOD, and RPMI) at 30 °C (Supplementary Fig. 3b). Subsequently, EV degradation was assessed by quantifying the number of EVs remaining in the conditioned media from each growth condition. In line with the results for B. cereus EVs, S. aureus Newman EVs were degraded in LB and hfRPMI, but not in MOD and RPMI (Supplementary Fig. 3b), suggesting that distinct but conserved factors influence EV degradation in bacteria.

Compositional traits of EVs are associated with distinctive EV degradation dynamics
Still, it is unclear whether secreted bacterial factors released into the conditioned media or specific compositional features of EVs contribute to the degradation or stability of the EVs. To investigate this further, EVsLB or EVsMOD were each spiked into cell-free conditioned EV-depleted LB and MOD, and EV degradation was assessed (Fig. 1i, j). Notably, EVsLB were significantly prone to degradation in both environments, whereas EVsMOD remained stable (Fig. 1j). This suggests that EVsLB degradation is directly linked to the EV composition. In order to gain insights into the molecular components of EVs and their modulation over time in the two different environments, Fourier-transform infrared spectroscopy (FTIR) was employed (Fig. 1k). FTIR is a high-resolution vibrational spectroscopic technique that provides detailed insight into the molecular composition of biological samples25,26. Based on stretching and bending vibrations of functional groups of the molecular constituents, encompassing lipids, proteins, polysaccharides and nucleic acids, global molecular fingerprints can be generated14,27. Chemometric analysis of spectral data recorded from EVsLB and EVsMOD revealed that the cultivation medium exerts the highest impact on the overall composition of the EVs. Principal component analysis (PCA) showed that PC1, which is associated with the growth medium, accounts for 61.9 % of the variance. It is noteworthy that PC2 (explaining 27.1 % of the variance) further differentiates EVsLB based on the sampling time point into two clusters. One cluster was constituted by EVs from 6 h and 9 h, while the EVs from 12 h and 15 h formed a separate, distinctive cluster. In contrast, EVsMOD from all four sampling points clustered together, indicating that the composition of EVsMOD does not undergo significant alteration over time (Fig. 1k). These results emphasise that the compositional traits of EVsLB and EVsMOD follow distinctive dynamics, prompting further analysis through untargeted proteomics and lipidomics.

Proteome remodelling reflects EV degradation in LB
To investigate the potential impact of EV degradation on the B. cereus EV proteome, we performed an untargeted LC-MS/MS proteomic analysis of EVsLB and EVsMOD harvested from bacterial cultures after 9 h and 15 h. A list of identified proteins is provided in supplementary data 1 (Supplementary Data 1). The majority of proteins in EVsLB are uniquely present at 9 h, while most EVsMOD proteins are present at both time points (Fig. 2a, b). PCA was performed on label-free quantification (LFQ) intensity data for unsupervised multivariate statistical analysis. Samples were primarily clustered by medium along PC1 (PC1, 60.5 %; Fig. 2c), with EVsLB also diverging into clusters based on cultivation time along PC2 (PC2, 23.4 %; Fig. 2c). In contrast, EVsMOD samples from both cultivation time points clustered together. This is in line with the results from FTIR spectroscopic analysis (Fig. 1k), which support the notion that the EVLB compositional profile undergoes dynamic changes. The high number of differentially regulated proteins (DEPs) observed between the EVsLB 9 h and EVsLB 15 h proteomes pinpoints the impact of EV degradation on the EV proteome (Supplementary Fig. 4a). On the contrary, EVsMOD proteomes show only minor changes between 9 h and 15 h (Supplementary Fig. 4b). The list of proteins included in the differential abundance analysis is provided in supplementary data 2 (Supplementary Data 2). The DEPs in B. cereus EVsLB, compared to B. cereus EVsMOD, determined at two different timepoints (9 h and 15 h; Supplementary Fig. 4c, d), were subjected to Gene Ontology (GO) enrichment analysis. This resulted in the identification of enriched pathways for each comparison. Because the GO hierarchy contains many redundant or overlapping terms, a redundancy-reduction step was applied to obtain a non-redundant set of pathways. Redundant GO terms were identified using a semantic similarity–based clustering implemented in the Python workflow with GOATOOLS28. The enriched pathways, cleared of duplicate and redundant terms, were visualised using a Sankey Diagram (Fig. 2d). This analysis revealed an overlap in enriched pathways at 9 h and 15 h in EVsMOD, but not in EVsLB. In summary, these results indicate active proteome remodelling in EVLB but not in EVMOD.

Growth environment impacts EV lipid architecture deciphered by lipidomics
Since the lipid bilayer directly interacts with the extravesicular milieu, and EV degradation has been found to depend on culture conditions, we hypothesised that the lipid bilayer may play a distinctive role during this process. Thus, we next carried out untargeted lipidomic analysis of EVs.

This analysis revealed a distinctive lipid bilayer composition of EVsLB and EVsMOD. A total of 544 lipid species for EVsLB and 311 lipid species for EVsMOD were identified. The list of identified lipids is presented in supplementary data 3 (Supplementary Data 3). Among all lipid species, a total of 295 lipid species were shared between EVsLB and EVsMOD (Fig. 3a). Lipid species were further classified based on the LIPID MAPS® Lipid Classification System into four lipid classes: fatty acyls (FAs), glycerolipids (GLs), glycerophospholipids (GPs) and sphingolipids (SPs). Analysis of sterols, prenols, saccharolipids and polyketides was omitted, since less than two lipid species were detected. The lipid composition of EVs was characterised through the quantification of the relative abundances of individual lipid species. This analysis revealed a predominance of sphingolipids in the EVsLB lipidome, comprising 78.36 % of the total lipid composition. This contrasts with the EVsMOD lipidome, which contains 0.08 % sphingolipids (Fig. 3b, Table 1). Specifically, sphingomyelins and glycosphingolipids were only detected in EVsLB but not in EVsMOD. To further investigate the sphingomyelin content in B. cereus EVs, a quantitative sphingomyelin assay was performed, revealing a dose-dependent increase in sphingomyelins in EVsLB, whereas EVsMOD did not contain any detectable sphingomyelins (Supplementary Fig. 5a). To rule out contaminations from potentially pelletable particles in LB, we quantified sphingomyelin in sterile LB and sterile, ultracentrifuged LB (LB*) (Supplementary Fig. 5b). Both media showed similar sphingomyelin levels, indicating the absence of sphingomyelin-positive pelletable particles (Supplementary Fig. 5b).

The near absence of sphingolipids in EVsMOD resulted in major compositional shifts in the other lipid classes (Fig. 3b), as 73.44 % of the EVsMOD lipidome consists of glycerolipids. The observed differences in the lipid compositions of EVsLB and EVsMOD were confirmed by chemometric analysis of FTIR data (Fig. 3c, Supplementary Fig. 6a). Subtraction spectra analysis revealed significant differences between EVsLB and EVsMOD in regions specific to sphingolipids and glycerolipids (Fig. 3c). These findings were further corroborated by the analysis of the loading plot that separates the samples based on media along PC1 (Supplementary Fig. 6b). In conclusion, EVsLB and EVsMOD exhibit substantial differences in their lipid architecture, which may be associated with their distinct susceptibility to degradation processes.

Sphingolipid composition dictates susceptibility to SMase-driven EV degradation
Due to the elevated levels of sphingolipids, in particular sphingomyelins, found in EVsLB, we hypothesised that a specific sphingomyelin-degrading enzyme secreted by B. cereus might be responsible for EV degradation. Given that B. cereus is known to secrete a sphingomyelinase (SMase, sphingomyelin phosphodiesterase; EC 3.1.4.12; see also Supplementary Fig. 7a)29,30, which hydrolyses sphingomyelin to phosphocholine and ceramide, we investigated whether B. cereus SMase could be a possible driver of EV degradation. To achieve this, we employed four complementary approaches. First, to test whether B. cereus SMase can degrade its sphingolipid-rich EVsLB, sterile LB was spiked with EVsLB and treated with commercially available B. cereus SMase (Fig. 4a, b). We observed a significant degradation of EVsLB in the presence of SMase, indicating that B. cereus SMase can indeed degrade EVsLB (Fig. 4b). Next, we investigated whether endogenously secreted SMase could be inhibited, thereby stopping EV degradation (Fig. 4c, d). To inhibit SMase activity in cell-free conditioned LB media, we used the SMase inhibitor Imipramine. Indeed, adding Imipramine to cell-free conditioned LB containing both endogenous EVs and endogenous SMase led to significantly reduced EV degradation (Fig. 4d). Except for Aprotinin, the protease inhibitors tested in parallel did not inhibit this temperature-dependent, enzyme-driven process as effectively as the SMase inhibitor Imipramine (Supplementary Fig. 7b-d). Next, to assess whether protease inhibitors affect B. cereus SMase activity, we measured SMase activity with a fluorometric enzyme activity assay in the presence of Imipramine, Aprotinin, EDTA and PMSF, respectively (Supplementary Fig. 7e). Imipramine strongly inhibited SMase activity, confirming its direct inhibition of B. cereus SMase. Furthermore, Aprotinin inhibited SMase activity to a lesser but significant extent, while PMSF did not show a significant effect in the SMase activity assay. Aprotinin and PMSF are both serine protease inhibitors; however, their mechanisms of action differ, which may account for their divergent effects on SMase activity and SMase-mediated EV degradation. Consistent with the weak effect on EV degradation (Supplementary Fig. 7d), EDTA showed only weak inhibition in the SMase activity assay (Supplementary Fig. 7e). Given that SMase activity is dependent on divalent cations such as Co2+ and Mg2+ 31, this weak inhibitory effect is likely to be associated with the chelation of divalent cations by EDTA32.

To confirm the specificity of Imipramine under our experimental conditions, we spiked sterile LB media with EVsLB and SMase. The addition of Imipramine blocked EV degradation, demonstrating that Imipramine specifically inhibits SMase activity (Supplementary Fig. 7f). Finally, we used an isogenic SMase knock-out mutant (Δsph) of B. cereus F4810/72 to produce cell-free conditioned LB medium lacking endogenous SMase. Conditioned LB medium created from the mutant Δsph and its parental wild type (WT) was depleted of EVs and subsequently spiked with EVsLB originating from the WT (Fig. 4e, f). The lack of SMase in the bacterial extracellular environment significantly reduced EV degradation (Fig. 4f). In summary, the results from these three complementary approaches foster our hypothesis that SMase plays a pivotal role in EV degradation.

To rule out the possibility of differential protease activity being the underlying cause of this effect, zymography was conducted using gelatin and casein substrates. This analysis revealed no significant differences in the proteolytic activity between the WT and the Δsph exoproteomes (Supplementary Fig. 7g). To confirm the pivotal role of SMase in EV degradation, we tested whether the lack of SMase would also impede EV degradation in continuously grown cultures (Fig. 4e, g). The WT and the Δsph mutant were cultivated in LB. The EV yields were assessed before EV degradation was observed in LB after 7h (t0) and then compared to EV yields after 10 h (t1) and 13 h (t2). As expected, EV yields decreased in WT bacterial cultures after prolonged cultivation but remained stable in Δsph bacterial cultures, indicating that the observed EV decline can be attributed to the presence of SMase in the bacterial exoproteome (Fig. 4e, g).

To exclude the possibility that co-purified factors may affect EV degradation, EVsLB were further purified by density gradient ultracentrifugation (EVsLB-DG). In addition, to rule out the possibility that LB-derived particles interfere with the EV degradation experiments, EVs from B. cereus grown in ultracentrifuged LB (LB*) were harvested by ultracentrifugation (EVsLB*) and further purified by density gradient ultracentrifugation (EVsLB*-DG). Subsequently, EVsLB and EVsLB* were used in spike-in experiments. Both EVsLB-DG and EVsLB*-DG, were spiked into sterile LB, sterile LB supplemented with external SMase, or sterile LB containing both external SMase and Imipramine, and the results were compared to those from spike-in experiments with EVsLB and EVsLB* (Supplementary Fig. 8a). Irrespective of the method used for B. cereus EV preparation, EV degradation was observed exclusively in the presence of SMase and was inhibited by Imipramine. No significant differences were observed in the extent of SMase-mediated EV degradation between EVsLB, EVsLB*, EVsLB-DG, and EVsLB*-DG (Supplementary Fig. 8a). Furthermore, EVs purified by density gradient centrifugation were tested positive for sphingomyelins (Supplementary Fig. 8b). Similar amounts of sphingomyelin were observed in EVsLB-DG, EVsLB*-DG, EVsLB, and EVsLB*. These findings demonstrate that density gradient-purified B. cereus EVs have the same sphingomyelin-positive lipid architecture and SMase susceptibility as crudely purified B. cereus EVs (Supplementary Fig. 8a, b). Consequently, these results reinforce the observation presented in figure 1b (Fig. 1b) and demonstrate that the degradation of EVsLB requires two factors: a sphingolipid-rich EV architecture and the presence of SMase within the extravesicular milieu.

Stress signatures distinguish EVsMOD from EVsLB
To elucidate the physiological implications of EV degradation, bacterial growth behaviour was profiled by calculating the maximum growth rate (Fig. 5a, Supplementary Fig. 9a) and the time to reach stationary phase (Fig. 5b, Supplementary Fig. 9a). Both parameters indicated that the nutrients in LB are consumed at a faster rate, as growth in LB was characterised by a significantly higher growth rate and a substantially shorter time to reach the stationary phase (Fig. 5a, b, Supplementary Fig. 9a). The response to these divergent environments manifested in different growth capacities and distinct compositions of the EV-cargo (Fig. 2d; Supplementary Fig. 4a-d). Therefore, we examined the proteomics dataset generated in this study from B. cereus EV (Supplementary Data 1; EVsLB 9h, EVsLB 15h, EVsMOD 9h, EVsMOD 15h) for proteins associated with environmental adaptation (Fig. 2). To obtain a comprehensive profile of the stress response proteome, the GO annotations for biological processes were first retrieved for all identified B. cereus EV proteins. Subsequently, the proteins associated with the parent GO term ‘response to stimuli’ (GO:0050896) and its child terms (descendant terms in the GO hierarchy structure) were selected. The intensities of the selected proteins were visualised in the heat-map depicted in Fig. 5c. This analysis revealed a total of 25 proteins that diverged into two distinct groups of stress-associated proteins (Fig. 5c). Notably, these two groups of proteins mirror the two particular growth conditions. The first group, exclusively enriched in EVsMOD, contained proteins associated with translational and oxidative stress, such as the DEAD-box ATP-dependent RNA helicase CshA and CshB, as well as the DNA repair protein RecN, and the superoxide dismutases SodA2 and SodC. The second group, exclusively enriched in EVsLB, comprised proteins associated with nutritional stress (DNA protection during starvation protein 1 (Dps1) and 2 (Dps2), putative carbon starvation protein A). Generally, translational and oxidative stress are tightly linked, and the enrichment of these proteins in EVsMOD implies that MOD-cultivated bacteria are exposed to translational and oxidative stress. While those translational and oxidative stress proteins are barely abundant in EVsLB, the exclusive enrichment of Dps1, Dps2 and the putative carbon starvation protein A in EVsLB suggests that bacteria cultivated in LB experience nutritional stress33–35.

Translational stress in MOD-grown bacteria was also supported by the increase in the mass spectrometric intensity of proteins associated with RNA binding in EVsMOD (Fig. 5d). To validate this finding, we performed a transcriptomic profiling of 9 h EVs (Fig. 5e, Supplementary Data 5). This analysis revealed an increased abundance of rRNA in EVsMOD (Fig. 5e), corroborating the proteomic data. Given that the semantic GO-term-based profiling of stress-associated proteins indicated the presence of both translational and oxidative stress in EVsMOD (Fig. 5c), we further examined oxidative stress levels in bacteria (Fig. 5f, g, Supplementary Fig. 9b, c). Bacteria were grown for 15 h in LB and MOD, and reactive oxygen species (ROS) in bacterial cells were determined using CellROX™ Staining and fluorescence microscopy (Fig. 5f, Supplementary Fig. 9b, c). As expected, significantly higher signals were measured for MOD-cultured bacteria than for LB-cultured bacteria (Fig. 5g). These results suggest that MOD-cultured bacteria experience oxidative and translational stress, while LB-cultured bacteria are facing nutritional stress, which is reflected in the proteomes of the respective EVs. Taken together, the specific EV lipid architecture combined with the particular EV cargo may indicate divergent functions of the respective EVs.

Bacterial growth benefits from endogenous SMase-degradable EVs as nutrient reservoirs
The concurrent presence of three starvation proteins (Fig. 5c, Supplementary Data 4) and the accelerated bacterial growth imply that bacteria grown in complex, growth-promoting environments, such as LB (Fig. 5a, b), deplete nutrient resources more efficiently and faster than bacteria grown in nutrient-scarce, mineral-based media such as MOD.

Since EV degradation only occurred in LB cultures but not in MOD cultures, we hypothesised that LB-cultivated bacteria could utilise the EVs components to boost their growth. To test this hypothesis, we exposed bacteria that had been pre-cultivated for 7 h in LB or MOD (t0) to either cell-free EV-depleted conditioned media or cell-free conditioned media containing endogenous bacterial EVs (Fig. 6a, b). The OD600 was measured after 5 h (t1) and 11 h (t2) of prolonged growth to calculate the relative growth rate (Fig. 6a-c). The relative growth rate t1-t2 was significantly higher in LB media containing endogenous bacterial EVs compared to EV-depleted LB (Fig. 6c). In contrast, in MOD media the presence of EVs did not significantly impact the bacterial growth rate (Fig. 6c). These findings emphasise a context-dependent role for sphingomyelin-rich EVs in promoting bacterial proliferation.

To further support the notion that EVs can be utilised as a nutrient resource, we leveraged the auxotrophy of B. cereus F4810/72 for valine36. Since the valine concentration in complex, nutrient-rich media cannot be controlled, we prepared MOD medium containing only minimal amounts of valine (0.7 mM), corresponding to 10 % of the valine concentration in the standard MOD medium, designated MODVal*. MODVal* was inoculated with SMase-producing WT bacteria and spiked with either EVsLB or EVsMOD (Fig. 6d, e). This approach revealed that only EVsLB can counterbalance the valine deficiency in MODVal*, emphasising that bacteria can utilise EVsLB as recyclable nutrient resources, whereas EVsMOD cannot. To provide further evidence that the interplay of SMase and EVsLB is required to rescue bacterial growth, we subsequently used the SMase-deficient Δsph mutant for spike-in experiments in MODVal* (Fig. 6f, g). The Δsph mutant was cultivated in the presence of SMase, EVsLB, or both in combination. As expected, the Δsph mutant was unable to utilise EVsLB to rescue the growth impairments observed in MODVal*. It is only through the introduction of external SMase that the valine deficiency in MODVal* can be compensated for and growth impairments overcome (Fig. 6f, g).

In summary, these data demonstrate that SMase-mediated EV degradation is integral for bacterial nutrient acquisition and adaption.

Methods
Bacterial strains
Experiments in this study were conducted using the emetic B. cereus reference strain F4810/7270 (aka AH187) and an isogenic SMase knock-out mutant (Δsph) of B. cereus F4810/7230. For complementary experiments, the B. cereus strains BC435, F588/94, and WBSC10925, as well as the Staphylococcus aureus strain Newman were used.

Growth media, production of conditioned media and EV-depleted conditioned media
The composition of the growth media LB71, MOD72. and MODVAL* is detailed in Supplementary Data 6. The host-factor-enriched RPMI (hfRPMI) was produced by growing Caco-2 cells in RPMI (Thermo Scientific, Waltham, MA, USA), supplemented with 10 % FBS (Thermo Scientific, Waltham, MA, USA), for 21 days as described earlier73. Subsequently, this hfRPMI was subjected to ultracentrifugation overnight at 180,000 × g to deplete the medium from Caco-2 EVs and then frozen until further use.

Ultracentrifuged sterile LB (LB*) was prepared by sterile-filtering LB (0.45 µm) and ultracentrifugation for 16 h at 180,000 × g. To obtain ‘cell-free conditioned media’, bacteria were grown for 7 hours at 30 °C while shaking (120 rpm) in the respective media and the supernatants were cleared of bacterial cells by a series of centrifugation steps: 3000 x g, 4000 x g, 4 °C, 15 min each, followed by filtration (pore size 0.45 µm), and centrifugation at 10,000 x g, (4 C°C, 15 min). To further produce ‘EV-depleted cell-free conditioned media’, cell-free conditioned media were ultracentrifuged overnight (16 h, 180,000 x g).

Production and isolation of EVs
For the production of EVs, bacteria were grown in the respective media at 30 °C, the commonly used B. cereus growth temperature, and 120 rpm shaking as described previously74. The cultures were then harvested at the indicated time points. To isolate EVs, the 100 ml culture was centrifuged (3,000 × g for 15 min; at 4 °C; 4,000 × g for 15 min; at 4 °C). Supernatants were filtered through a 0.45 µm filter (Merck Millipore, Darmstadt, Germany), and the filtrate was centrifuged at 10,000 × g for 15 min at 4 °C. Subsequently, EVs were pelleted from this supernatant via ultracentrifugation, at 180,000 × g for one hour using OptiSeal Polypropylene tubes (MLA-50 rotor, Optima MAX-XP, Beckman-Coulter, Brea, CA, USA). The supernatant was discarded, and the pellet was resuspended in 30 µl PBS (pH 7.4) for every 100 ml of bacterial liquid culture.

Density gradient ultracentrifugation of EVs
EVs were further purified using a density gradient (DG) of 12 % to 60 % OptiPrep (Iodixanol; Sigma-Aldrich, St. Louis, MO, USA), as described previously19. OptiPrep was diluted in PBS (2 ml/fraction), 5.6x109 EVs/ml were loaded on top and subsequently subjected to ultracentrifugation at 180,000 x g for 16 h at 4 °C (MLA-50 rotor, Optima MAX-XP, Beckman-Coulter, Brea, CA, USA). The single fractions were collected, diluted with PBS to 15 ml and the OptiPrep reagent was removed by Amicon filter columns (100 kDa cut-off, Sigma-Aldrich, St. Louis, MO, USA). Each fraction was centrifuged twice for 30 min at 10,000 x g, at 4 °C. The resulting concentrated sample was diluted to a final volume of 300 µl PBS and analysed for the particle number and size. Fractions containing EVs (F2-F4) were pooled and stored at –20 °C for further use.

Characterisation of EVs
Nanoparticle tracking analysis (NTA)
To quantify the amount and size of isolated particles, NTA was performed using a PMX-230 TWIN Laser ZetaView (Particle Metrix, Inning, Germany) with a temperature setting of 25.0 °C, with sensitivity and shutter set to 70. Recordings were analysed using ZetaView 8.04.02 software (Particle Metrix, Inning, Germany).

Transmission electron microscopy (TEM) and atomic force microscopy (AFM)
Transmission electron microscopy was employed to visualise EVs, utilising either the drop-on-grid method or the preparation of ultra-thin sections of resin-embedded EVs. For the drop-on-grid method, EVs were resuspended to reach a final concentration of 2x108/µl, of which 10 µl were incubated for 60 min on formvar/carbon copper grids (300 mesh, FCF300H-CU-SB, Science Services, Munich, Germany). Samples were then fixed with 1 % glutaraldehyde (5min) in PBS, washed in ddH2O, followed by negative staining with 2 % aqueous uranyl acetate for 5 min. To prepare resin-embedded EV samples, EVs were pelleted and then overlaid with glutaraldehyde to preserve their morphology. Ultra-thin sections of EV samples were prepared as described previously14. Grids and resin-embedded ultra-thin B. cereus EV sections were examined using a transmission electron microscope (EM 900, Zeiss, Jena, Germany) equipped with a slow-scan CCD 2K- wide-angle dual-speed camera (TRS, Moorenweis, Germany).

To acquire AFM images, previously established protocols were followed75,76. In short, 5 μg of EVs were immobilised for 60 min in 100 μl PBS on 0.01 % poly-L-lysine coated mica slides. The scanning was performed using a Dimension FastScan Bio (Bruker, Billerica, MA, USA) with a SCANASYST-FLUID+ tip (Bruker, Billerica, MA, USA) and a spring constant of 0.7 N/m. Before the start of the AFM measurement, the tip was calibrated using a mock-immobilised slide with PBS only. After scanning the sample, the images were processed using Gwyddion77.

Fourier-transform infrared spectroscopy (FTIR)
To assess compositional changes in EVs, FTIR spectroscopy was employed as described previously14,78. For the FTIR measurement, EVs sampled from three independent bacterial cultures were applied in technical quadruplicates to a 384-well silicon plate (Bruker Optics GmbH, Ettlingen, Germany). After drying the samples (40 °C, 20 min), FTIR spectra were recorded in transmission mode (spectral range: 4,000–500 cm-1; spectral resolution: 6 cm-1)79,80, using an HTS-XT microplate adapter coupled with a Tensor 27 FTIR spectrometer (Bruker Optics GmbH, Ettlingen, Germany). For univariate analysis, technical replicates were averaged, subjected to vector normalisation and baseline correction. The subtraction spectrum of EVsMOD - EVsLB was calculated based on 2nd order derivative spectra. In the obtained spectra data, regions corresponding to sphingolipids81 (2,800–3,000 cm-1, 1,600–1,680 cm-1, 1,260 cm-1, 1,455–1,485 cm-1, 1,000–1,110 cm-1), glycerolipids82 (1,728–1,742 cm-1), and phospholipid vibrations83 (1,070–1,260 cm-1) were highlighted. For multivariate analysis, technical replicates were averaged, and then pre-processed by baseline correction, L2 normalisation, spline interpolation, smoothing with a Savitzky-Golay filter, and calculation of the second-order derivatives. For univariate processing of FTIR spectral data OPUS software version 7.2 (Bruker Optics GmbH, Ettlingen, Germany) was used. Multivariate FTIR spectral processing, analysis and visualisation were performed by Python (version 3.11.0) using Pandas (version 2.2.3), Numpy (version 1.26.4), Matplotlib (version 3.8.4)84, scipy (version 1.15.1)85, and Scikit-learn (version 1.6.1)86 libraries.

Assessment of EV degradation
To assess EV degradation, different types of media were used: sterile media spiked with bacterial EVs, cell-free conditioned media containing endogenous bacterial EVs (produced as described above), and EV-depleted cell-free conditioned media spiked with bacterial EVs. To measure EV degradation, the media containing spiked-in EVs (1.5 x 109 EVs/ml - 2.5 x 1010 EVs/ml) or endogenous EVs were incubated at 30 °C and 120 rpm for 4.5 h, unless stated otherwise. NTA was used to determine the amount of EVs at the start of the experiment (t0) and after 4.5 h or at the indicated time points.

To test the potential of exogenously added SMase to degrade EVs, B. cereus SMase (0.125 U/ml, Sigma-Aldrich, St. Louis, MO, USA) was added to sterile culture media spiked with B. cereus EVs. The following substances were used to test whether EV degradation can be inhibited: Imipramine (700 µg/ml), Pepstatin (5 µg/ml), Aprotinin (14 µg/ml), PMSF (7 µg/ml), EDTA (150 mg/ml, all Sigma-Aldrich, St. Louis, MO, USA).

SMase Activity Assay
SMase activity was measured in conditioned EV-depleted B. cereus media, for which bacteria were grown for 7 h at 30 °C. The Amplex® Red Sphingomyelinase Assay Kit (Waltham, MA, USA) was used to determine the production of sphingomyelinase, as described previously30. In brief, 10 µl of conditioned EV-depleted media was mixed with 1x reaction buffer, provided by the manufacturer, to reach a final volume of 100 µl. A working solution containing 2 U/ml horseradish peroxidase, 0.2/ml choline oxidase, 8 U/ml alkaline phosphatase and 0.5 mM sphingomyelin was prepared. Finally, 100 µl of the sample diluted in 1x reaction buffer was mixed with 100 µl of the previously prepared working solution in a black clear-bottom 96-well plate (Greiner, Kremsmünster, Austria). Fluorescence was measured after 30 min (excitation 530 nm; emission 590 nm).

Sphingomyelin Quantification Assay
Sphingomyelin levels were quantified in EVs and in sterile bacterial culture media using a fluorometric sphingomyelin assay kit (Sigma-Aldrich, St. Louis, MO, USA), according to the manufacturer’s instructions. In brief, EV protein content was determined, and samples were either adjusted to the indicated EV protein amount or to 15 µg total EV protein. EV samples were then diluted in the supplied assay buffer to a final volume of 50 µl per well. For analysis of bacterial culture media, 50 µl of media was used per well. A working reagent containing SMase reaction buffer and SMase working stock was prepared and mixed with the samples, following the manufacturer’s instructions, and incubated for 2 h at 37 °C, protected from light. Subsequently, 50 µl of the sphingomyelin assay mixture (containing enzyme mix, red detection reagent, and assay buffer) was added to the samples and the plate was incubated for 1 h at room temperature. Subsequently, fluorescence was recorded (excitation 535 nm; emission 587 nm). A positive control supplied by the manufacturer (100 µM sphingomyelin) was included on each plate and assayed in parallel with a blank. Fluorescence values were corrected by subtracting the blank signal from all samples and controls.

Quantitative proteomics using mass spectrometry
B. cereus EVs were analysed by quantitative proteomics using mass spectrometry at the Bavarian Centre for Biomolecular Mass Spectrometry (BayBioMS) at TU Munich. To obtain EVs, B. cereus cultures were grown in LB or MOD for 9 and 15 hours, at 30 °C while shaking (120 rpm). EVs were collected by using ultracentrifugation, as described in the previous section. For sample preparation, the volume equivalent to 15 µg of EV protein was combined with 4 x Laemmli buffer (BioRad, Hercules, CA, USA), 2-mercaptoethanol (Sigma-Aldrich, St. Louis, MO, USA) and 10 x RIPA lysis buffer (Merck, Darmstadt, Germany). PBS was added to a final volume of 26 µl. To disrupt EVs, samples were frozen at -80 °C overnight. After thawing, samples were incubated at 70 °C for 5 minutes, followed by sonication for 5 minutes in an ice-cold water bath. For proteomic analysis, in-gel trypsin digestion was performed as described previously87. EV-proteins were separated on Nu-PAGE™ 4–12% Bis-Tris protein gels (Thermo Scientific, Waltham, MA, USA) for approximately 1 cm, after which the accumulated protein band was cut out, following reduction (50 mM dithiothreitol), alkylation (55 mM chloroacetamide), and digestion overnight with trypsin (Trypsin Gold, mass spectrometry grade, Promega, WI, USA). Samples were dried and subsequently resuspended in 25 μl of buffer A (2% acetonitrile, 0.1% formic acid in HPLC-grade water), of which 5 μl were injected for the mass spectrometry (MS) measurement. Liquid Chromatography (LC)–MS/MS measurements were carried out on a Dionex Ultimate 3,000 RSLCnano system coupled to a Q-Exactive HF-X mass spectrometer (Thermo Fisher, Waltham, MA, USA). Injected peptides were delivered to a trap column (ReproSil-our C18-AQ, 5 μm, Dr. Maisch, 20 mm × 75 μm, self-packed) following transfer to an analytical column (ReproSil Gold C18-AQ, 3 μm, Dr. Maisch, 450 mm × 75 μm, self-packed) and separated using a 50 min gradient from 4 to 32 % of solvent B (0.1 % FA, 5 % DMSO in acetonitrile) in solvent A (0.1 % FA, 5% DMSO in HPLC grade water) at 300 nl/min flow rate. The Q-Exactive HF-X mass spectrometer was operated in data-dependent acquisition and positive ionisation mode, as described previously87. Using MaxQuant software 1.6.3.488 with its integrated Andromeda search engine89, peptides were identified, quantified and matched by the MS2 spectra matched against the B. cereus AH187 proteome from Uniprot (UP000002214), along with common contaminants.

Trypsin/P was selected as the proteolytic enzyme, and carbamidomethylated cysteine was set as a fixed modification. Variable modifications included methionine oxidation and protein N-terminal acetylation. The FDR – set to 0.01 for peptide spectrum matches and proteins – was obtained using a target-decoy method with reversed protein sequences. LFQ intensities were subsequently analysed using Perseus version v2.0.10.088. To identify proteins that were consistently detectable across different media and time points, we filtered the data using the function ‘filter rows based on valid values’ set to ’50 % in at least one group’. Missing values were handled through imputation based on a normal distribution, using Perseus’s default parameters (width = 0.3, down shift = 1.8). The imputed dataset was normalised by quantile normalisation before statistical testing. Volcano plots were created by plotting the log FC against the −log10 adjusted p-values for each pairwise comparison. PCA was obtained using LFQ intensities and the AMICA platform90 (https://bioapps.maxperutzlabs.ac.at/app/amica).

The proteomics data have been deposited to the ProteomeXchange Consortium with the following identifier PXD065751.

Enrichment analysis
Gene ontology and enrichment analyses were performed using ShinyGO v0.80 (http://ge-lab.org/go/), with the reference organism B. cereus91. Significantly enriched GO terms with adjusted p-value with false discovery rate (FDR) < 0.005 were included for further analysis. Python plotly and goatools libraries were used for GO term redundancy removal and visualisation using a Sankey diagram.

To reduce redundancy, redundant GO terms were removed using hierarchical filtering via the goatools library, which leverages the GO-directed acyclic graph (DAG) structure from the go-basic.obo ontology to retain only the most specific (child) terms.

To refine the GO terms, a semantic similarity-based filtering step using a weighted Jaccard index and gene annotation-derived information content (IC) was applied for each condition92. Pairs of terms exceeding the similarity threshold (threshold = 0.7) were filtered, retaining only the term with the higher information content (IC) from each pair. The filtering was performed independently for each condition. To validate the robustness of the weighted Jaccard approach, the results were compared with those produced using Resnik and Lin similarity metrics, yielding comparable reductions. For visualisation of condition-specific enrichment and flow patterns, Sankey diagrams were implemented to map the relationships. This layered design facilitates the inspection of both shared and condition-specific pathway–gene relationships. To perform HCA analysis and to illustrate the heat map, the following tool was used93: http://www.heatmapper.ca. To obtain hierarchical clusters, the following settings were used: Clustering Method: Average Linkage and Distance Measurement: Kendall’s Tau. The proteins depicted in the heat map were chosen based on GO terms. Stress response proteins were identified by filtering for proteins with child-terms of the ‘response to’ GO-term.

Transcriptomics
To isolate RNA from EVs, for each sample 100 ml of bacterial culture was prepared by growing bacteria for 9 h at 30 °C while shaking (120 rpm). EVs that were collected by ultracentrifugation from the entire culture volume (100 ml) were used, and RNA was isolated using the Monarch® Total RNA Miniprep Kit (New England BioLabs, Ipswich, MA, USA). Instructions for tough-to-lyse samples, such as bacteria, yeast, and plants, were followed. For the library preparation, the CORALL RNA-Seq V2 kit (Lexogen, Vienna, Austria) was used, following the protocol for short insert sizes. No rRNA depletion or mRNA enrichment was performed prior to preparing this library. The size distribution of the final libraries was evaluated via capillary electrophoresis using the DNA 1000 Assay on the Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). Sequencing was performed using 100 sequencing cycles on a NovaSeq 6000 platform (Illumina, San Diego, CA, USA) with a single-end 150 bp (SE150) format. The genomes of AH187 and NVH0075-95 served as reference genomes. Prior to alignment, all reads were trimmed to remove adapter sequences. Both before and after trimming, sequencing quality was assessed using FastQC94. The trimmed reads were then aligned to the reference genome using Bowtie's "best" algorithm95. The resulting Bowtie output was processed to evaluate read counts using HTSeq with the intersection_nonempty mode96.

The transcriptomics data have been deposited to European Nucleotide Archive with the following accession number PRJEB94405.

Quantitative lipidomics using mass spectrometry
The lipidome of B. cereus EVs was analysed by quantitative lipidomics via mass spectrometry at the Metabolomics Core Facility at EMBL Heidelberg. For the EV lipid extraction, B. cereus was grown in LB or MOD for 9, at 30 °C while shaking (120 rpm), and EVs were collected via ultracentrifugation, as described in the previous section. To extract EV-lipids, equal amounts of EVs (1.2 × 109) were pelleted and resuspended in 150 µl of ice-cold isopropanol (Carl Roth, Karlsruhe, Germany) containing internal standards (provided by the EMBL Metabolomics Core Facility). The samples were incubated on ice for 20 minutes, followed by 5 minutes of vortexing and centrifugation at 14,000 × g for 15 minutes at 4 °C. The supernatant containing the extracted lipids was subsequently frozen until further analysis. A quality control (QC) sample was prepared by pooling 20 µl from each sample together. LC-MS/MS analysis of the extracted lipids was performed on a Vanquish UHPLC system coupled to a Q-Exactive plus HRMS (Thermo Scientific, Waltham, MA, USA) in both ESI positive and negative mode78. In brief, lipid and fatty acid separation was carried out on a Kinetec C18 column (1x100; 2.6 μM; flow rate 0.26 ml/min; 30 °C). Solvents were buffered either with 10 mM ammonium formate (positive mode) or 10 mM ammonium acetate (negative mode). Solvents were further supplemented with 0.1% formic acid in isopropanol:acetonitrile (9:1) for mobile phase A, and 0.1% formic acid in water:acetonitrile (6:4) for solvent B. Lipid detection was carried out with a HRMS full scan at a mass resolving power of R = 70,000 and a range of 200-1,500 m/z. Data-dependent MS/MS scans were collected using full scans with higher energy collisional dissociation (HCD) at a mass resolving power of R = 17,500. MS parameters in the Tune software were set as follows: spray voltage, 3,200 V; capillary temperature, 280 °C; probe heater temperature, 300 °C; sheath gas, 30 units; auxiliary gas, 5; S-Lens RF level, 60 units. During data acquisition, data-dependent tandem mass spectra were obtained for the top 10 most intense precursors. Samples were randomised for LC-MS/MS analysis sequence, and the pooled quality control samples, along with the blank samples, were injected at the beginning of the sample analysis sequence to stabilise the LC-MS/MS system. A quality control sample was injected after every six samples to monitor the instrument's stability (%CV < 20). The chromatograms were evaluated, and the stability of quality control samples was checked with PCA plots before proceeding with further data analysis. Thermo Xcalibur software (Thermo Scientific, Waltham, MA, USA) was employed to acquire data and perform preliminary data evaluation, including assessment of chromatogram quality and obtaining extracted ion chromatograms peak integration and raw data visualisation. Alignment of LC-MS/MS data, peak picking, adduct deconvolution, and normalisation were done using Progenesis QI (Waters, Nonlinear Dynamics, Newcastle upon Tyne, UK) software. Lipid annotations were performed using LipidBlast database and EMBL Metabolomics Core Facility spectral library (http://curatr.mcf.embl.de) for MS and MS/MS-based identification. The mass tolerance in MS1 and MS2 was 5 ppm and 10 ppm, respectively.

To analyse differentially expressed lipids and lipid abundance, files from both negative and positive measurement modes were combined to avoid counting duplicates or lipids that are measured in both modes. Next, the average of all quality control (QC) samples was calculated for each lipid. Then, we compared QC lipid values between positive and negative modes, selecting only the mode with the higher value for further analysis. Duplicates were removed by keeping the replicate with the higher value. Finally, both modes were combined into a single list, ensuring each lipid had only one respective measurement.

To annotate the lipid class and subclass, the metabolomics workbench, available at www.metabolomicsworkbench.org97 was used. To determine the number of abundant lipid species, we considered lipids to be abundant in a replicate only if their detected value exceeded the blank. With three biological replicates analysed per condition, lipids were only counted as abundant if present in at least two out of three biological replicates. Subsequently, we quantified the relative proportions of each lipid class and subclass.

The lipidomics data have been deposited to MetaboLights repository with the study identifier MTBLS1326098.

Reactive oxygen species assay
To assess accumulation of ROS in bacterial cells, the CellROX™ Orange Reagent (Thermo Scientific, Waltham, MA, USA) was utilized following the manufacturer’s protocol with minor modifications. Briefly, bacterial cells were cultivated for 15 h in either 100 ml LB or MOD at 30 °C. From this culture, 1 ml was used to assess ROS accumulation. After pelleting (3000 x g, 15 min, room temperature (RT)) the bacterial pellet was washed once with 0.9 % NaCl, following incubation with CellROX™ Orange Reagent (10 µM) at 37 °C for 60 minutes. An unstained control sample was prepared to account for autofluorescence. After staining, the cells were washed three times with 0.9 % NaCl, spotted on a slide and dried overnight. Imaging was performed using a bright-field and wide-field fluorescence microscope (Carl Zeiss, Oberkochen, Germany) with a deep orange filter, and Zeiss ZEN Blue software was applied for image acquisition. The mean fluorescence intensity of the acquired images was assessed using ImageJ99. Images were converted to 8-bit formats to enable thresholding of signal intensities in regions of interest (ROI).

Zymography
EV-depleted cell-free conditioned LB derived from WT and Δsph bacteria were tenfold concentrated using Amicon spin-filters (10 kDa, Sigma-Aldrich, St. Louis, MO, USA). Of this concentrate, 1 µl was loaded onto a 12.5 % SDS-PAGE gel supplemented with 1 % casein or 1 % gelatine (both Sigma-Aldrich, St. Louis, MO, USA). Proteins were separated for 2 h at 120 V, with a maximum of 20 mA at 4 °C. Thereafter, gels were regenerated using 2.5 % Triton X-100 and subsequently equilibrated with first 5 mM CaCl2, 50 mM Tris (pH 7.4; 20 min; Carl Roth, Karlsruhe, Germany) and second 0.2 M NaCl, 10 mM CaCl2, 50 mM Tris, 0.02 % Brij35 (pH 7.4; 20-30 h; Carl Roth, Karlsruhe, Germany). The gel was stained overnight at RT using PageBlue Protein staining (Thermo Scientific, Waltham, MA, USA) and destained with ultrapure water100.

Assessing the effect of EVs on bacterial growth dynamics
Bacterial growth in LB and MOD media was analysed by modelling growth dynamics using a modified Gompertz101 function:
OD600(t) = A * exp{-exp[ (μm*e / A) * (λ-t) + 1]}

A is the maximum OD600, μm is the maximum specific growth rate, λ is the lag time, and e is Euler’s number. Initial parameters were derived from raw data and refined using the Solver tool in Microsoft Excel, which minimised the sum of squared differences between the observed OD values and the predictions of the Gompertz model.

To assess the impact of EVs on bacterial growth, cell-free conditioned LB and cell-free conditioned MOD media were prepared as described above. While one part of each media was left unmanipulated (EVs+), the other part was subjected to EV-depletion (EVs-) in order to remove endogenously produced EVs. The following day, bacteria were grown for 7 h at 30 °C, 120 rpm (100 ml, Erlenmeyer flasks) and subsequently subjected to media exchange (t0). Therefore, bacteria were harvested by centrifugation (5,000 x g, 3 min, RT), resuspended in previously prepared pre-warmed EV-containing conditioned medium (EVs+) or EV-depleted conditioned medium (EVs-) and further incubated at 30 °C, 120 rpm. Growth of the bacteria was measured as OD600 and the relative growth rate (average change in OD600/hour) was calculated between t1 (5 h) and t2 (11 h) after medium exchange at t0.

An automated bacterial growth curve recorder (Bioscreen Pro, Bio Laboratories, Singapore) was used to investigate the recycling of EV components by bacteria. Bacteria (either B. cereus F4810/72 WT or its isogenic Δsph mutant) were inoculated in technical quadruplicates in the respective culture media in 100-well honeycomb plates (Thermo Scientific, Waltham, MA, USA) and grown for 12 h at 30 °C with orbital shaking. For spike-in experiments, equal amounts of EVsLB or EVsMOD (1.7 x 109 EVs/ml) were used and 0.125 U/ml of B. cereus SMase (Sigma-Aldrich, St. Louis, MO, USA) were added. Bacterial growth was measured as OD600 every 5 min and every 10th data point is shown for visualisation. The area under the curve (AUC) was calculated using the GraphPad Prism (Prism 10 for macOS, Version 10.4.2) plug-in.

Statistical analysis
Statistical analysis was performed with Prism 10 for macOS, Version 10.4.2. One-way or two-way ANOVA followed by Bonferroni’s multiple comparisons test was used when more than two groups were compared. An unpaired two-tailed t-test was used when comparing two groups. All graphs display individual data points and mean value with standard deviation (SD). Details of the statistical tests used are shown in the respective figure legends. P-values smaller than or equal to 0.05 were considered significant.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this study the authors present novel data demonstrating that bacteria can utilize extracellular vesicles as a nutrition source under certain conditions. The ability to utilize EVs as a nutrition source is dependent on two factors (i) the lipid composition of the EV membrane and (ii) the ability of the bacteria to secrete an enzyme that degrades the EV, thus releasing its contents. Overall the experiments are well performed and appropriate controls are included. There are a number of places where additional controls would have increased rigor of the study and I have outlined those below. The idea that EVs may function as a nutritional storage system is novel and the data presented support the hypothesis that this may be possible under certain circumstances. Since this is a novel hypothesis I feel it's important the authors provide a more detailed discussion about how this impacts our knowledge of bacterial communities and the role of EVs (see comment below).\nThe title of the manuscript is somewhat vague and cryptic. Perhaps consider rephrasing “provides new clues on bacterial vesicle function” with something like “suggests a role for EVs in nutrient storage/recycling”?\nLine 107: “…were found to be larger than EVsMOD”. Please be specific. How much larger were they?\nThe results shown in supplemental fig 2d and e are important to the study and should be moved to the main manuscript.\nLine 144: “The dynamics of bacterial EV production were monitored…”. Can the authors clarify if EV production, EV degradation, or both was measured in this assay?\nLine 178: “To assess whether EV degradation manifests in the particular proteomes…” Please rephrase/clarify the meaning here, it is unclear.\nLine 165: When FTIR spectroscopy is first introduced in the manuscript it would be useful to include a sentence or two outlining what this technique is used for to assist readers who are not familiar with the approach.\nLine 173: Fig 1g should be Fig 1i\nLine 178: “To assess whether EV degradation manifests in the particular proteomes…” Please rephrase this sentence as the meaning is unclear.\nLine 188: “The volcano plot visualises exclusive enrichment of proteins at 9 h in EVSLB (Supplementary Fig. 4a-d), further supporting the hypothesis that EVsLB degrade over time (Supplementary Fig. 4a)”. I don’t see how the data presented in volcano plots supports these statements. The data in Supplementary Fig. 4a seems to indicate a roughly equivalent number of proteins are more abundant at 15 hours and 9 hours. Can the authors clarify?\nPlease explain the origin of the data in figure 2D in more detail. The figure legend says it was constructed using differentially regulated proteins from the comparison presented in supplementary Figure 4 which helps, however only minimal details are given in the manuscript text. Please also explain what is meant by “The enrichment of non-redundant pathways” on line 192\nIn several places throughout the manuscript the term “plain LB” is used. Does this refer to sterile unused LB? If so please clarify and use the term “sterile LB” instead.\nAn important control is missing from Fig 4B. The SMase inhibitor (imipramime) should have been added along with exogenous SMase to show specific inhibition of SMase activity restores EV degradation.\nLine 257: “Various protease inhibitors tested in parallel did not inhibit this temperature-dependent, enzyme-driven process as effectively as the SMase inhibitor Imipramine.” This statement is misleading and is not supported by the results in supplemental figure 6b. Results in supplemental fig 6b show that addition of proteases did significantly inhibit EV degradation and in some cases (aprotinin) this inhibition appears to be comparable to or more than that observed with SMase inhibitor (imipramime). This needs to be explained/discussed in more detail. The iss\nFig 4 a, c, and e. The schematics for each experiment are actually somewhat confusing and don’t really add to the figure. At the bottom of each diagram the symbols used are depicted presumably as a “key” for the figure. However, at first it appears that they are part of the schematic figure itself. Perhaps enclosing them in a box would make this more obvious and help with clarity of the figure. Fig 4e in particular is not helpful as It doesn’t outline the experiment well (should indicate which is the deltasph mutant).\nThe result in supplemental fig 6f is quite important to the overall study and should perhaps be moved to the main manuscript.\nFig 5a and b. Could the authors provide this data as a plot of growth (OD600 Vs time) as supplemental data as this is the format most researchers are familiar with for bacterial growth.\nLine 297: “we screened the proteome data…” What proteome data are they referring to? Is it the data generated in this study (depicted in Fig 2?). If so this needs to be clearly stated. Also, how was the data screened? More details need to be provided.\nLine 299: “(child-terms of the ‘response to’ GO-term Supplementary Table 4)”. What is meant by this statement? The meaning is unclear.\nLine 309: “the exclusive enrichment of Dps1, Dps2 and the putative carbon starvation protein A in EVsLB indicates that bacteria cultivated in LB experience nutritional stress.” Can the authors clarify whether they believe EV cargo proteins are present simply because that are simultaneously abundant in the cytoplasm of the originating cell, or if they believe proteins are selectively “loaded” into EVs. Also, the word “indicates” should be substituted with “suggests”.\nLine 410: “It can be assumed”. Suggest changing this to “we hypothesize”\nLine 441: “The latter is supported by EVsMOD proteomic data…” Perhaps the authors could also discuss how the EV RNA data could support the idea of EVMOD have an alternative function.\nDiscussion: The authors propose a novel model whereby EV's represent a form of nutrient storage for subsequent utilization by the bacteria when nutrients become limited. While this is a novel proposal the discussion of this hypothesis is underdeveloped and should be expanded. What are the evolutionary advantages of extracellular storage of nutrients compared to intracellular storage? If EVs serve as a nutrient reservoir, would they not also be accessible to other bacterial species? What are the potential implications for this (in a microbiome setting). Couldn’t EV’s diffuse away from/be washed away from the bacterial cells (particularly during infection)? Can the authors clarify if they feel nutrient storage is the primary function of EVs or just one of a number of functions. I think these points and many others should be incorporated into the discussion.\nLine 488: “For the production of EVs, bacteria were grown in the respective media at 30 °C”. Were both B. cereus and S. aureus strains grown at 30°C? Can the authors explain the reason behind their decision to grow the bacteria at 30 °C? Is this the most commonly used temperature for B. cereus growth? How would EV membrane lipid composition be impacted if B. cereus was grown at 37°C compared to 30°C? Growth of S. aureus is typically performed at 37 °C and EV composition in S. aureus has been shown to be temperature dependent (as is membrane lipid composition), therefore some explanation regarding the decision why this temperature was chosen should be given.\nNone of the data sets generated (proteomic/transcriptomic/lipidomic) have been deposited at an online database and made available to reviewers. This should have been done prior to manuscript submission. This data must be made available.", "reviewer_2": "In this paper, the authors examine the degradation of MVs and their role as a nutrient source. The turnover of MVs is a highly important topic particularly in terms of understanding their mobility and function but remains largely unexplored. I believe the aim of this study offers new insights into MV stability. However, several critical points need clarification, and the manuscript may be misleading due to insufficient discussion of key information. Notably, based on the current experiments and data, it is difficult to determine whether the authors are analyzing free sphingolipids or yeast EV originating from LB medium, or true bacterial MVs that have incorporated sphingolipids. If the strain does not produce sphingolipids and considering the data showing that the EVs in LB medium mainly consist of sphingolipids, the most logical conclusion is that the authors are examining EVs derived from the medium (from yeast), rather than bacterial MVs. Below are specific comments.\nMajor comments\n1. The authors mention very briefly in the discussion (line 444 ) that this bacterium does not produce sphingolipids. This information is very important but is hidden in the manuscript and should be clearly stated at the beginning of the manuscript. Whether the strain the authors used produces sphingolipids or not in the used condition will directly impact the interpretation of the entire dataset.\n2. Do the authors have any evidence that the strain they used do not produce sphingolipids? To my knowledge, B. cereus in general do not produce sphingolipids, but I am unfamiliar of the strain the authors used. Whether this strain produce sphingolipids or not is a critical point which is not examined. Adding lipidomic data of the cells in table 1 will be useful in discussing the differences of the lipidomes of cells and MVs, and the medium if necessary to estimate which lipids comes from the medium. In addition, As commented further below, it is essential to purify the MVs instead of using the crude precipitation sample in analyzing the MV composition.\n3. Most importantly, given that the sphingolipids are likely coming from the LB medium, it is critical to purify MVs with density gradient ultracentrifugation. Without purification, the authors may be analyzing LB-derived free sphingolipid or yeast EVs rather than bacterial MVs. Furthermore, it is critical to show that the sphingolipid is truly associated with bacterial MVs to reach the conclusion of this manuscript. Since over 70% of the lipidome in MVs(LB) consist of sphingolipids, it is possible that the majority of EVs in this condition is yeast derived EVs with bacterial MVs being a minor population.\n4. The authors should analyze LB medium without bacterial inoculation and examine the \"MV fraction\" from this control. This would help determine whether the observed effects are due to bacterial MVs or to yeast extract–derived EVs or free sphingolipids present in the medium.\n5. If bacterial MVs are involved and the strain do not produce sphingolipids, the overall data is suggesting that the MV lipid composition can be altered by extracellular lipid but is not well investigated. The authors should examine whether sphingolipid can be incorporated in MVs (or if bacterial MVs become associated with yeast EVs).\n6. Related to the point above the authors indicate in Fig. 7 and elsewhere that the MVs derived from LB consist of sphingolipids and other lipids. If the EV mainly consist of sphingolipids, it could be degraded but if sphingolipid is not a major component, I guess the particle may remain intact. I fully understand it is challenging to see the lipid composition in a single particle but the heterogeneity of EVs should be taken into consideration.\n7. It is unclear how the MVs were quantified, for example in fig. 1b. were the MVs first isolated and then counted ? If only crude precipitation was used without further purification, other particles such as flagella could be present and might be included in the NTA counts. This should be clarified.\n8. It is better to show TEM image of a wider view rather than showing one image of a particle. From the image provided it is hard to tell if they are EV or not. Better images might be obtained if ultrathin sections are not used."}, "author_response": "We thank the reviewer for the posi>ve feedback. Further, we appreciate the construc>ve comments, which have helped improve our manuscript. As suggested, addi>onal controls have been included, and a paragraph has been added to the discussion that addresses the poten>al impacts of the newly discovered func>on of bacterial EVs as a nutri>onal resource on bacterial communi>es and on the role of EVs. Responses to all comments are indicated in blue, and changes to the manuscript are highlighted in yellow.\nPlease refer to the sec>on below for our point-by-point response.\nThe <tle of the manuscript is somewhat vague and cryp<c. Perhaps consider rephrasing “provides new clues on bacterial vesicle func<on” with something like “suggests a role for EVs in nutrient storage/recycling”?\nAuthor response: We thank the reviewer for this sugges>on and changed the >tle accordingly.\nLines 1-2: Sphingomyelinase-mediated extracellular vesicle degrada>on suggests a role of EVs in nutrient recycling.\nLine 107: “…were found to be larger than EVsMOD”. Please be specific. How much larger were they?\nAuthor response: We revised the following sec>on on line 107 and added details about the EV size.\nLines 104-107: Nanopar>cle tracking analysis (NTA; Supplementary Fig. 2g) was used to assess the size of EVs. EVs (NTA: 195.3 nm) were found to be larger than EVs (NTA: 142.3 nm), resul>ng in a LB MOD size difference of 53.0 nm, which was validated by isola>ng EVs from three addi>onal pathogenic B. cereus strains (Supplementary Fig. 2g).\nAuthor response: We appreciate the valuable feedback. As requested, we incorporated the Supplementary Fig. 2d and 2e into Fig. 1 of the main manuscript. Accordingly, these figures are now Fig. 1g and Fig. 1h. We also updated the numbering of the following figures and the legends for Fig. 1 and for Supplementary Fig. 2.\nLine 144: “The dynamics of bacterial EV produc<on were monitored…”. Can the authors clarify if EV produc<on, EV degrada<on, or both was measured in this assay?\nAuthor response: To clarify this point, we have revised this statement on B. cereus as well as the respec>ve statement on S. aureus in the manuscript as follows:\nLines 126-128: The number of B. cereus EVs was monitored in bacterial cultures grown in parallel in hfRPMI and uncondi>oned RPMI.\nLines 134-137: To test whether EV degrada>on is specific for B. cereus EVs, or whether it also occurs in other bacteria, Staphylococcus aureus Newman was cultured in different growth media (LB, hfRPMI, MOD, and RPMI) at 30 °C (Supplementary Fig. 3b). Subsequently, EV degrada>on was assessed by quan>fying the number of EVs remaining in the condi>oned media from each growth condi>on.\nLine 178: “To assess whether EV degrada<on manifests in the par<cular proteomes…” Please rephrase/clarify the meaning here, it is unclear.\nAuthor response: We apologise for this unclear phrasing and revised the manuscript as follows:\nLines 165-168: To inves>gate the poten>al impact of EV degrada>on on the B. cereus EV proteome, we performed an untargeted LC-MS/MS proteomic analysis of EVs and EVs harvested from LB MOD bacterial cultures a`er 9 h and 15 h.\nLine 165: When FTIR spectroscopy is first introduced in the manuscript it would be useful to include a sentence or two outlining what this technique is used for to assist readers who are not familiar with the approach.\nAuthor response: Done as suggested.\nThe following informa>on on FTIR was included:\nLines 150-154: FTIR is a high-resolu>on vibra>onal spectroscopic technique that provides detailed insight into the molecular composi>on of biological samples25,26. Based on stretching and bending 2 vibra>ons of func>onal groups of the molecular cons>tuents, encompassing lipids, proteins, polysaccharides and nucleic acids, global molecular fingerprints can be generated14, 27.\nLine 173: Fig 1g should be Fig 1i\nAuthor response: We thank the reviewer for poin>ng out the issue with the subfigure labelling. As Fig. 1 was modified in response to the aforemen>oned comment, the subfigure leaering has also been updated accordingly.\nLine 178: “To assess whether EV degrada<on manifests in the par<cular proteomes…” Please rephrase this sentence as the meaning is unclear.\nAuthor response: We rephrased the sentence as follows:\nLines 165-168: To inves>gate the poten>al impact of EV degrada>on on the B. cereus EV proteome, we performed an untargeted LC-MS/MS proteomic analysis of EVs and EVs harvested from LB MOD bacterial cultures a`er 9 h and 15 h.\nLine 188: “The volcano plot visualises exclusive enrichment of proteins at 9 h in EVSLB (Supplementary Fig. 4a-d), further suppor<ng the hypothesis that EVsLB degrade over <me (Supplementary Fig. 4a)”. I don’t see how the data presented in volcano plots supports these statements. The data in Supplementary Fig. 4a seems to indicate a roughly equivalent number of proteins are more abundant at 15 hours and 9 hours. Can the authors clarify?\nAuthor response: We agree that the wording may have led to an overes>ma>on of the volcano diagrams in rela>on to EVs . We changed the text accordingly.\nLB\nIt now reads as follows:\nLines 177-179: The high number of differen>ally regulated proteins (DEPs) observed between the EVs 9 h and EVs 15 h proteomes pinpoints the impact of EV degrada>on on the EV proteome LB LB (Supplementary Fig. 4a).\nPlease explain the origin of the data in figure 2D in more detail. The figure legend says it was constructed using differen<ally regulated proteins from the comparison presented in supplementary Figure 4 which helps, however only minimal details are given in the manuscript text. Please also explain what is meant by “The enrichment of non-redundant pathways” on line 192\nAuthor response: We appreciate the reviewer's feedback and have accordingly expanded the data origin details for Fig. 2d in the main manuscript text and clarified the meaning of the sentence in line 192.\nIn several places throughout the manuscript the term “plain LB” is used. Does this refer to sterile unused LB? If so please clarify and use the term “sterile LB” instead.\nAuthor response: Done as requested.\nPlain LB changed to sterile LB, throughout the manuscript and in the supplement. Lines: 108, 231, 546, 553 and 1096\nAn important control is missing from Fig 4B. The SMase inhibitor (imipramime) should have been added along with exogenous SMase to show specific inhibi<on of SMase ac<vity restores EV degrada<on.\nAuthor response: We agree that this control is important and have performed the experiment as requested (see new Supplementary Fig. 7f). While the addi>on of SMase alone resulted in degrada>on of EVs, the simultaneous addi>on of Imipramine effec>vely inhibited SMase-mediated EV degrada>on.\nThe following paragraph was incorporated into the results sec>on:\nLines 251-253: To confirm the specificity of Imipramine under our experimental condi>ons, we spiked sterile LB media with EVs and SMase. The addi>on of Imipramine blocked EV degrada>on, LB demonstra>ng that Imipramine specifically inhibits SMase ac>vity (Supplementary Fig. 7f).\nLine 257: “Various protease inhibitors tested in parallel did not inhibit this temperature-dependent, enzyme-driven process as effec<vely as the SMase inhibitor Imipramine.” This statement is misleading and is not supported by the results in supplemental figure 6b. Results in supplemental fig 6b show that addi<on of proteases did significantly inhibit EV degrada<on and in some cases (apro<nin) this inhibi<on appears to be comparable to or more than that observed with SMase inhibitor (imipramime). This needs to be explained/discussed in more detail. The iss\nAuthor response: We apologise for this misleading statement and have included addi>onal experimental data for clarifica>on.\nFurthermore, Apro>nin inhibited SMase ac>vity to a lesser but s>ll significant extent, while PMSF did not show a significant effect in the SMase ac>vity assay. Apro>nin and PMSF are both serine protease inhibitors; however, their mechanisms of ac>on differ, which may account for their divergent effects on SMase ac>vity and SMase-mediated EV degrada>on. As it has been reported previously that the ac>va>on of SMase depends on certain serine proteases (DOI: 10.1096/fasebj.11.8.9240970), it is temp>ng to speculate that the inhibitory effect of Apro>nin is linked to the SMase ac>va>on cascade. However, further research will be necessary to decipher the mode of ac>on of Apro>nin on SMase ac>vity. The slight inhibi>on of EV degrada>on by PMSF is likely aaributable to indirect effects rather than specific SMase inhibi>on. Consistent with the weak effect on EV degrada>on (Supplementary Fig. 7d), EDTA showed only weak inhibi>on in the SMase ac>vity assay (see new Supplementary Fig. 7e). This weak inhibitory effect is likely to be associated with the chela>on of divalent ca>ons by EDTA (DOI: 10.1002/mrc.5009), given that SMase ac>vity is dependent on divalent ca>ons such as Co2+ and Mg2+ (DOI 10.1074/jbc.M601089200). Overall, these results indicate that understanding the interac>ons between protease inhibitors and B. cereus SMase will require a more systema>c, mechanis>c approach, which is clearly beyond the scope of the current study.\nThe following statement is now included in the manuscript:\nLines 238-250: Except for Apro>nin, the protease inhibitors tested in parallel did not inhibit this temperature-dependent, enzyme-driven process as effec>vely as the SMase inhibitor Imipramine (Supplementary Fig. 7b-d). Next, to assess whether protease inhibitors affect B. cereus SMase ac>vity, we measured SMase ac>vity with a fluorometric enzyme ac>vity assay in the presence of Imipramine, Apro>nin, EDTA and PMSF, respec>vely (Supplementary Fig. 7e). Imipramine strongly inhibited SMase ac>vity, confirming its direct inhibi>on of B. cereus SMase. Furthermore, Apro>nin inhibited SMase ac>vity to a lesser but significant extent, while PMSF did not show a significant effect in the SMase ac>vity assay. Apro>nin and PMSF are both serine protease inhibitors; however, their mechanisms of ac>on differ, which may account for their divergent effects on SMase ac>vity and SMase-mediated EV degrada>on. Consistent with the weak effect on EV degrada>on (Supplementary Fig. 7d), EDTA showed only weak inhibi>on in the SMase ac>vity assay (Supplementary Fig. 7e). Given that SMase ac>vity is dependent on divalent ca>ons such as Co2+ and Mg2+ 31, this weak inhibitory effect is likely to be associated with the chela>on of divalent ca>ons by EDTA32.\nFig 4 a, c, and e. The schema<cs for each experiment are actually somewhat confusing and don’t really add to the figure. At the bogom of each diagram the symbols used are depicted presumably as a “key” for the figure. However, at first it appears that they are part of the schema<c figure itself. Perhaps enclosing them in a box would make this more obvious and help with clarity of the figure. Fig 4e in par<cular is not helpful as It doesn’t outline the experiment well.\nAuthor response: We have modified the figure accordingly.\nAs suggested, the symbols used were enclosed in a box and Fig. 4e was reworked. Furthermore, Supplementary Fig. 6f was moved from the supplement to the main figure (see following comment) and was integrated into Fig. 4 (now Fig. 4g).\nThe result in supplemental fig 6f is quite important to the overall study and should perhaps be moved to the main manuscript.\nAuthor response: Done as requested.\nWe moved Supplementary Fig. 6f to the main manuscript and integrated it into Fig. 4 (now Fig. 4e, g). We have also included a corresponding experimental schema>c (see comment above).\nFig 5a and b. Could the authors provide this data as a plot of growth (OD600 Vs <me) as supplemental data as this is the format most researchers are familiar with for bacterial growth.\nAuthor response: Done as requested.\nWe have included the corresponding OD600 growth curve in the supplement (Supplementary Fig. 9a). .\nLine 297: “we screened the proteome data…” What proteome data are they referring to? Is it the data generated in this study (depicted in Fig 2?). If so this needs to be clearly stated. Also, how was the data screened? More details need to be provided.\nAuthor response: We have reworked the sec>on and included more details on the data genera>on and screening. The proteomics dataset generated in this study from B. cereus EVs (PXD065751) was uploaded to ShinyGo (haps://bioinforma>cs.sdstate.edu/go/) and assigned to gene ontology (GO) terms. The assigned GO terms were searched for the parent term ‘response to s>muli’ (GO:0050896) and its subordinate terms (descendant terms in the GO hierarchy structure, aka child terms).\nThe following statement was added:\nLines 297-304: Therefore, we examined the proteomics dataset generated in this study from B. cereus EV (Supplementary Table 1; EVs 9h, EVs 15h, EVs 9h, EVs 15h) for proteins associated with LB LB MOD MOD environmental adapta>on (Fig. 2). To obtain a comprehensive profile of the stress response proteome, the GO annota>ons for biological processes were first retrieved for all iden>fied B. cereus EV proteins. Subsequently, the proteins associated with the parent GO term ‘response to s>muli’ (GO:0050896) and its child terms (descendant terms in the GO hierarchy structure) were selected. The intensi>es of the selected proteins were visualised in the heat-map depicted in Fig. 5c.\nLine 299: “(child-terms of the ‘response to’ GO-term Supplementary Table 4)”. What is meant by this statement? The meaning is unclear.\nAuthor response: Done.\nThis sec>on has been reworded to clarify and now reads as follows (see also comment to Line 297 above):\nLines 300-304: To obtain a comprehensive profile of the stress response proteome, the GO annota>ons for biological processes were first retrieved for all iden>fied B. cereus EV proteins. Subsequently, the proteins associated with the parent GO term ‘response to s>muli’ (GO:0050896) and its child terms (descendant terms in the GO hierarchy structure) were selected. The intensi>es of the selected proteins were visualised in the heat-map depicted in Fig. 5c.\nLine 309: “the exclusive enrichment of Dps1, Dps2 and the puta<ve carbon starva<on protein A in EVsLB indicates that bacteria cul<vated in LB experience nutri<onal stress.” Can the authors clarify whether they believe EV cargo proteins are present simply because that are simultaneously abundant in the cytoplasm of the origina<ng cell, or if they believe proteins are selec<vely “loaded” into EVs.\nAuthor response: Although proteins such as Dps1, Dps2 and CstA were enriched in EVs , we do not LB interpret this as evidence for an ac>ve or selec>ve loading mechanism. Instead, their presence in EVs likely reflects the protein composi>on of the parental cell (protein abundance and spa>al LB organisa>on) at the moment the EVs were formed. Therefore, we believe that enrichment of these nutri>onal stress-associated proteins in EVs is due to passive loading. Nevertheless, we cannot LB exclude the possibility of a hitherto unknown ac>ve, selec>ve loading mechanism.\nAlso, the word “indicates” should be subs<tuted with “suggests”.\nAuthor response: Done as requested. (Line 315)\nLine 410: “It can be assumed”. Suggest changing this to “we hypothesize”\nAuthor response: Changed as suggested. (Line 376)\nAuthor response: We thank the reviewer for this sugges>on and have included the following paragraph in the discussion:\nLine 395-404: Thus, it is temp>ng to speculate that EVs have different func>ons, such as media>ng MOD stress signals. The laaer is supported by B. cereus EVs proteomic data, which suggests that MOD- MOD grown bacteria face transla>onal and oxida>ve stress. The stress response reflected by the EVs is MOD further supported by the increased abundance of ribosomal proteins and rRNA in EVs . Since MOD bacteria lack strict compartmentalisa>on, they depend on a >ghtly regulated proteostasis to control protein produc>on, folding, and transport. Exposure of bacteria to stressful and harsh environments results in an imbalance between transcrip>on and transla>on44–46. Consequently, it is temp>ng to speculate that the loading of excess rRNA into EVs enables the bacterial cell to fine-tune its MOD transla>onal landscape. However, further research is necessary to determine the poten>al role of EVs in transla>onal regula>on in bacteria.\nDiscussion: The authors propose a novel model whereby EV's represent a form of nutrient storage for subsequent u<liza<on by the bacteria when nutrients become limited. While this is a novel proposal the discussion of this hypothesis is underdeveloped and should be expanded. What are the evolu<onary advantages of extracellular storage of nutrients compared to intracellular storage? If EVs serve as a nutrient reservoir, would they not also be accessible to other bacterial species? What are the poten<al implica<ons for this (in a microbiome sekng). Couldn’t EV’s diffuse away from/be washed away from the bacterial cells (par<cularly during infec<on)? Can the authors clarify if they feel nutrient storage is the primary func<on of EVs or just one of a number of func<ons. I think these points and many others should be incorporated into the discussion.\nAuthor response: We thank the reviewer for the remarks on our discussion. We do not believe that nutrient storage is the primary or exclusive func>on of EVs, but rather one of several cri>cal func>onal roles, as e.g., EVs are also secreted but do not play a significant role in EV-mediated nutrient MOD recycling. We have expanded the discussion sec>on, taking into account the poten>al effects of selec>ve EV degrada>on and elabora>ng on the benefits and trade-offs of extracellular or intracellular nutrient storage. We do hope that our work, particularly the new aspects included in the extended discussion, inspires the scientific community to explore further the role of EVs in bacterial communities and bacterial-environmental interactions.\nThe newly introduced sec>on reads as follows:\nLines 419-441: From an evolu>onary perspec>ve, extracellular nutrient storage in EVs provides a mechanism for bacterial popula>ons to buffer transient nutrient limita>on, extending beyond the 8 confines of the individual cell. By this mechanism, bacterial EVs can support not only the producing cell but also neighbouring bacteria sharing the same environment, thereby promo>ng collec>ve survival under nutrient-limited condi>ons. Such EVs may act as ‘selec>vely accessible packages’, where only SMase-secre>ng bacteria, such as Clostridium perfringens, Listeria monocytogenes, and Staphylococcus epidermidis40, can access the stored nutrients, adding a layer of specificity within microbial communi>es. However, further research will be required to explore the extent to which this extracellular nutrient storage can be used as a public good by the en>re bacterial community or whether it confers a selec>ve advantage for the producing bacteria or par>cular members of the bacterial community. Extracellular storage inevitably carries the disadvantage of poten>al loss through diffusion or environmental clearance. Yet this diffusion can also be advantageous, e.g. by facilita>ng host-pathogen interac>ons by systemic dissemina>on of EVs11,15 or priming distant niches, similar to mechanisms described for EVs in cancer metastasis56. By contrast, intracellular storage allows rapid access to nutrients but restricts benefits to single cells, highligh>ng a trade-off between single-cell and community-level resource management strategies.\nSMase-mediated EV degrada>on also reframes current concepts of EV func>onali>es. EVs protect, package, and deliver a wide range of bioac>ve molecules14,37,57,58. By ac>vely modula>ng EV turnover, SMase impacts EV stability and specificity, and may also affect quorum sensing37, toxin delivery14, nutrient acquisi>on58 and DNA transfer59. Moreover, SMase-mediated EV degrada>on likely impairs EVs' ability to act as decoys against phages and an>bio>cs60,61. Deciphering the precise contribu>on of SMase-mediated EV degrada>on to the func>onal repertoire of EVs will be crucial to understanding how EV func>onality is integrated into the regulatory networks that shape bacterial communi>es.\nLine 488: “For the produc<on of EVs, bacteria were grown in the respec<ve media at 30 °C”. Were both B. cereus and S. aureus strains grown at 30°C? Can the authors explain the reason behind their decision to grow the bacteria at 30 °C? Is this the most commonly used temperature for B. cereus growth? How would EV membrane lipid composi<on be impacted if B. cereus was grown at 37°C compared to 30 °C? Growth of S. aureus is typically performed at 37 °C and EV composi<on in S. aureus has been shown to be temperature dependent (as is membrane lipid composi<on), therefore some explana<on regarding the decision why this temperature was chosen should be given.\nAuthor response: Indeed, 30 °C is the temperature commonly used for B. cereus research and diagnos>cs, as now men>oned in the Methods sec>on of the revised manuscript.\nLines 485-486: For the produc>on of EVs, bacteria were grown in the respec>ve media at 30 °C, the commonly used B. cereus growth temperature, and 120 rpm shaking as described previously74.\nWe agree that the EV membrane lipid composition might be temperature dependent. Therefore, we inves>gated the amount of sphingomyelin, the target of SMase, in B. cereus and S. aureus Newman EVs that were isolated from bacterial cultures grown at either 30 °C or 37 °C. This analysis revealed no significant difference in the sphingomyelin quan>ty between 30 °C and 37 °C in either B. cereus or S. aureus (Explanatory Fig. 1).\nExplanatory Fig. 1: Sphingomyelin levels of B. cereus and S. aureus EVs are similar between 30 °C and 37 °C. B. cereus and S. aureus were LB grown in LB at either 30 °C or 37 °C for 7 h, and EVs were harvested by differen>al ultracentrifuga>on. Subsequently, the sphingomyelin content was quan>fied using a commercially available fluorometric sphingomyelin quan>fica>on assay (as described in the Methods sec>on).\nNone of the data sets generated (proteomic/transcriptomic/lipidomic) have been deposited at an online database and made available to reviewers. This should have been done prior to manuscript submission. This data must be made available.\nAuthor response: We thank the reviewer for poin>ng this out and apologise for the inconvenience.\nAll datasets are uploaded and accessible for the reviewers using the following key:\nProteomics: haps://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD065751, reviewer account username: reviewer_pxd065751@ebi.ac.uk, password: 2kGLi3g78kdH\nLipidomics: haps://www.ebi.ac.uk/metabolights/editor/MTBLS13260/files?reviewCode=0 0816091-2cde-4f0b-b970-3c2275427ec8\nTranscriptomics: haps://www.ebi.ac.uk/ena/browser/view/PRJEB94405\nStatements pertaining to data availability have been incorporated into the respec>ve methods sec>ons.\nLines 621-622: The proteomics data have been deposited to the ProteomeXchange Consor>um with the following iden>fier PXD065751.\nLines 709-710: The lipidomics data have been deposited to MetaboLights repository with the study iden>fier MTBLS1326098.\nLines 660-661: The transcriptomics data have been deposited to European Nucleo>de Archive with the following accession number PRJEB94405.\nLines 769-779: Source Data are provided with this paper. The mass spectrometric raw files as well as the MaxQuant output files concerning proteomics have been deposited to the ProteomeXchange Consor>um via the PRIDE repository and can be accessed using the iden>fier PXD065751 (haps://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD065751), reviewer account username: reviewer_pxd065751@ebi.ac.uk, password: 2kGLi3g78kdH). The mass spectrometric raw files as well as the output files concerning lipidomics have been deposited to the MetaboLights repository with the study iden>fier MTBLS13260 (haps://www.ebi.ac.uk/metabolights/editor/MTBLS13260/files?reviewCode=00816091-2cde-4f0b- b970-3c2275427ec8). The transcriptomic data is deposited at European Nucleo>de Archive under the ENA Accession Number PRJEB94405 (haps://www.ebi.ac.uk/ena/browser/view/PRJEB94405) and is available during the review process.\nIn this paper, the authors examine the degrada<on of MVs and their role as a nutrient source. The turnover of MVs is a highly important topic par<cularly in terms of understanding their mobility and func<on but remains largely unexplored. I believe the aim of this study offers new insights into MV stability. However, several cri<cal points need clarifica<on, and the manuscript may be misleading due to insufficient discussion of key informa<on. Notably, based on the current experiments and data, it is difficult to determine whether the authors are analyzing free sphingolipids or yeast EV origina<ng from LB medium, or true bacterial MVs that have incorporated sphingolipids. If the strain does not produce sphingolipids and considering the data showing that the EVs in LB medium mainly consist of sphingolipids, the most logical conclusion is that the authors are examining EVs derived from the medium (from yeast), rather than bacterial MVs. Below are specific comments.\nWe thank the reviewer for the remarks and valuable sugges>ons. We especially appreciate that the research ques>on addressed in this work is considered highly relevant.\nFirstly, we would like to extend our apologies to the reviewer for not presen>ng the full kine>cs of EVs from B. cereus cultures in Fig. 1b. As the primary aim of our research pertains to the degrada>on of EVs, the ini>al presenta>on of data in Fig 1b was focused on the late growth phases of B. cereus.\nFrom the reviewer's inquiries concerning the poten>al implica>ons of EV yeast extract-derived EVs from the LB medium used for bacterial cul>va>on, we assume that not showing data from the early growth phase in Fig 1b has led to a misunderstanding regarding the origin of EVs, for which we apologise.\nEV yields from bacterial cultures at 0 h (directly a`er inocula>on) and a`er 3 h of cul>va>on have now been included in Fig. 1b of our revised manuscript. Addi>onally, as suggested by the reviewer, we performed NTA analyses of sterile growth media controls and incorporated the results into Fig. 1b. To this end, sterile LB and MOD were subjected to ultracentrifuga>on and poten>ally pelleted par>cles were analysed using NTA. No EV par>cles were detected, neither in the yeast-extract- containing LB nor in the defined mineral medium MOD. The revised Fig. 1b (depicted below for informa>on together with the experimental scheme Fig. 1a) shows the specific enrichment of bacterial EVs during the early growth phase and the absence of poten>al contamina>ng EVs origina>ng from the sterile media used for bacterial cul>va>on (LB, MOD). Specifically, a 70-fold increase in EV yields from B. cereus cultures was observed between 3 h and 6 h in both LB and MOD. Following a 6 h incuba>on period, a substan>al decline in EV yields was observed for B. cereus LB cultures, while a concomitant increase in EVs was evident for B. cereus MOD cultures. These results show that the observed effects in our experiments are aaributable to bacterial EVs, not to poten>al contamina>ng yeast-extract EVs or free sphingolipids in the media.\nThese findings, as well as the results of the addi>onal experiments suggested by the reviewer (see response to claims 3, 4, 8), conclusively demonstrate that bacterial EVs, not EVs derived from the medium (from yeast), are examined throughout our work. This conclusion is further supported by our EV proteome data, which demonstrate that 99.84 % of proteins are assigned to B. cereus, while 0.16 % are assigned to yeast (see Claim 3.2, Explanatory Fig. 3).\nWe hope this explana>on, along with the results from the addi>onal experiments, has clarified any open ques>ons. In summary, we believe that our manuscript has benefited from the inclusion of the proposed addi>onal controls and experiments.\nPlease find below our detailed response to each comment. Responses to all comments are indicated in blue, and changes to the manuscript are highlighted in yellow.\n1. The authors men<on very briefly in the discussion (line 444) that this bacterium does not produce sphingolipids. This informa<on is very important but is hidden in the manuscript and should be clearly stated at the beginning of the manuscript. Whether the strain the authors used produces sphingolipids or not in the used condi<on will directly impact the interpreta<on of the en<re dataset.\nAuthor response: We apologise for not clearly sta>ng this informa>on at the beginning of the manuscript.\nThe following statement is now included in the introduc>on:\nLines 55-61: Although progress has been made in understanding the func>ons of bacterial EVs, the role of the bacterial EV lipid bilayer remains poorly understood. For instance, sphingolipids are 13 repeatedly reported as major cons>tuents of bacterial EV lipid bilayers18-21. Yet, the majority of bacterial species, including B. cereus, are unable to synthesise sphingolipids de novo22,23. Nevertheless, they may be capable of scavenging sphingolipids from their environment24. Despite consensus on the presence of sphingolipids in bacterial EVs, their func>onal role within bacterial EV membranes remains to be elucidated.\n2. Do the authors have any evidence that the strain they used do not produce sphingolipids? To my knowledge, B. cereus in general do not produce sphingolipids, but I am unfamiliar of the strain the authors used. Whether this strain produce sphingolipids or not is a cri<cal point which is not examined. Adding lipidomic data of the cells in table 1 will be useful in discussing the differences of the lipidomes of cells and MVs, and the medium if necessary to es<mate which lipids comes from the medium. In addi>on, as commented further below, it is essen<al to purify the MVs instead of using the crude precipita<on sample in analysing the MV composi<on.\n2.1 Regarding the reviewer's ques<on about sphingolipid produc<on in B. cereus.\nAuthor response: Correct. B. cereus, including the B. cereus strain used in this study, does not belong to the group of sphingolipid-producing bacteria. The lipidomics analysis of B. cereus EVs presented in this study demonstrates that sphingolipids are detected only in the EV lipidome when they are present in the growth environment (see new Supplementary Fig. 5b). Consistently, no sphingolipids were detected in EVs derived from bacteria grown in sphingolipid-free media. The inability to synthesise sphingolipids de novo is a general feature reported for many bacterial taxa, including members of the phylum Firmicutes (aka Bacillota) (DOI: 10.1073/pnas.1001501107). To our knowledge, de novo sphingolipid biosynthesis has been described primarily in eukaryotes and in a limited number of bacterial species, such as the phylum Bacteroidetes, Chlorobibacteria, and subsets of Alpha- and Delta-Proteobacteria (DOI: 10.1073/pnas.1001501107, DOI: 10.3389/fmicb.2023.1289819,DOI: 0.1016/j.mib.2017.12.011, DOI: 10.1039/c8np00019k). That most bacteria, including B. cereus, are not able to produce sphingolipids is now men>oned in the introduc>on sec>on of the revised MS (Lines 55-61; see also answer to claim 1 above).\n2.2 Regarding the reviewer’s comment about the origin of sphingolipids.\nAuthor response: We agree with the reviewer that a comprehensive compara>ve lipidomic analysis of bacterial cells and culture media would be interes>ng; however, it would exceed the scope of the present study. The protocol used for EV lipid extrac>on for lipidomics is not suitable for bacterial cells. Thus, such a compara>ve analysis would require a different experimental procedure, which was beyond the scope of the current study.\nThus, we used three addi>onal approaches to address the origin of the sphingomyelins:\na) Spike-in experiments using fluorescently labelled sphingomyelin. B. cereus cultures were supplemented with a fluorescently labelled sphingomyelin (SM C11; 4 µM; C11 TopFluor™), extensively washed, and analysed by fluorescence microscopy, revealing membrane-associated fluorescence indica>ve of sphingomyelin uptake. Moreover, fluorescence measurements of isolated B. cereus EVs of those cultures confirmed the incorpora>on of SM C11 into the EVs (see for more details Claim 5; Explanatory Fig. 4a, b).\nThese experiments showed that B. cereus takes up sphingomyelins from the environment and incorporates them in EVs (for details, see answer to Claim 5 and the respec>ve Explanatory Fig. 4a, b).\nb) Quan<fica<on of sphingomyelin in media. To assess whether the sphingomyelin of bacterial EVs originates from sphingomyelin-scavenging of the EV-producing bacteria, we quan>fied the LB sphingomyelin content of the sterile cul>va>on media (LB, MOD). As expected, sterile LB was posi>ve, whereas MOD was tested nega>vely (see new Supplementary Fig. 5b). To exclude that the sphingomyelins detected in our lipidomic analysis of EVs derived from any poten>ally LB pelletable sphingomyelin-posi>ve par>cles in sterile LB, the sphingomyelin signal of sterile LB to sterile LB ultracentrifuged for 16 h, 180,000 x g (designated as LB*) was compared. No significant differences were detected between LB and LB* (see new Supplementary Fig. 5b). These results imply that a contamina>on of our bacterial EVs sample with the “LB-MV frac>on” (see claim 4) LB can be excluded, fostering the no>on that B. cereus can scavenge free sphingomyelins from the cul>va>on medium.\nc) Comparison of the sphingomyelin content of density gradient-purified EVs and crude EVs. This experiment showed that crude EVs and density gradient-purified EVs contain equal amounts of sphingomyelin (see new Supplementary Fig. 8b), further suppor>ng that sphingomyelin is an integral part of B. cereus EVs (see also response to claim 3).\nLB\nA new paragraph on the new supplementary experiments was introduced into the results sec>on\nThis paragraph reads as follows:\nLines 208-214: To further inves>gate the sphingomyelin content in B. cereus EVs, a quan>ta>ve sphingomyelin assay was performed, revealing a dose-dependent increase in sphingomyelins in EVs , LB 15 whereas EVs did not contain any detectable sphingomyelins (Supplementary Fig. 5a). To rule out MOD contamina>ons from poten>ally pelletable par>cles in LB, we quan>fied sphingomyelin in sterile LB and sterile, ultracentrifuged LB (LB*; Supplementary Fig. 5b). Both media showed similar sphingomyelin levels, indica>ng the absence of sphingomyelin-posi>ve pelletable par>cles (Supplementary Fig. 5b).\n3. Most importantly, given that the sphingolipids are likely coming from the LB medium, it is cri<cal to purify MVs with density gradient ultracentrifuga<on. Without purifica<on, the authors may be analyzing LB-derived free sphingolipid or yeast EVs rather than bacterial MVs. Furthermore, it is cri<cal to show that the sphingolipid is truly associated with bacterial MVs to reach the conclusion of this manuscript. Since over 70% of the lipidome in MVs(LB) consist of sphingolipids, it is possible that the majority of EVs in this condi<on is yeast derived EVs with bacterial MVs being a minor popula<on.\n3.1. Regarding the reviewer's sugges<on to include results from MVs purified with density gradient ultracentrifuga<on:\nIn order to address the research ques>on concerning the poten>al of bacterial EVs to serve as a nutrient reservoir, we are using crude EVs to simulate natural condi>ons. However, we agree with this reviewer that using EVs purified by density gradient ultracentrifuga>on would help to validate our findings and support our conclusions. Thus, as suggested, EVs were purified by means of density gradient ultracentrifuga>on (EVs ) and subjected to EV degrada>on experiments (see new LB-DG Supplementary Fig. 8a). For these experiments, EVs and EVs were spiked into sterile LB, sterile LB LB-DG LB LB-DG supplemented with external SMase, or sterile LB containing both external SMase and the SMase inhibitor Imipramine. The results from EV degrada>on experiments on EVs mirrored results LB-DG obtained from degrada>on experiments on crude EV prepara>ons (EVs ). Thus, it could be assumed LB that the SMase-mediated bacterial EV degrada>on described in this work is it is not caused by free sphingolipids present in the media.\nIn addi>on, EVs from bacteria grown in ultracentrifuged LB (LB*) were harvested by ultracentrifuga>on and further purified by density gradient ultracentrifuga>on (EVs ) to assess a LB*-DG poten>al impact of LB media -derived par>cles on EV prepara>ons. NTA analysis revealed a comparable size distribu>on for both EVs and EVs (Explanatory Fig. 2).\nLB-DG LB*-DG\nThe results from EV degrada>on experiments on EVs confirmed the results from the degrada>on LB*-DG experiments on crude EV prepara>ons (EVs and EVs ). Irrespec>ve of the method employed for EV LB LB* prepara>on, EV degrada>on was observed only in the presence of SMase and was inhibited by the SMase inhibitor Imipramine. No significant differences were observed in the extent of SMase- mediated EV degrada>on between EVs , EVs EVs , and EVs (new Supplementary Fig. 8a).\nLB LB*, LB-DG LB*-DG\nFurthermore, we tested EVs purified by density gradient centrifuga>on for sphingomyelins (new 16 Supplementary Fig. 8b). Similar amounts of sphingomyelin were observed in EVs , EVs , EVs , LB-DG LB*-DG LB and EVs , further suppor>ng that sphingomyelin is an integral part of B. cereus EVs (see also LB* LB response to claim 2).\nIn summary, the supplementary experiments conducted with purified EVs corroborated our results using crude EVs and further substan>ate our conclusions that bacterial EVs can undergo SMase- LB mediated EV degrada>on (see new Supplementary Fig. 8a, b). We thank the reviewer for this sugges>on.\nExplanatory Fig. 2: NTA analysis of density gradient (DG) purified EVs originaMng from B. cereus grown in LB and ultracentrifuged LB (LB*). NTA was used to assess the size- distribu>on of DG purified EVs (EVs and EVs ; n=3).\nLB-DG LB*-DG\nA new paragraph on the new supplementary experiments using density gradient purified EVs was introduced into the results sec>on (see Lines 269-284:).\nThis paragraph reads as follows:\nLines 269-284: To exclude the possibility that co-purified factors may affect EV degrada>on, EVs LB were further purified by density gradient ultracentrifuga>on (EVs ). In addi>on, to rule out the LB-DG possibility that LB-derived par>cles interfere with the EV degrada>on experiments, EVs from B. cereus grown in ultracentrifuged LB (LB*) were harvested by ultracentrifuga>on (EVs ) and further purified LB* by density gradient ultracentrifuga>on (EVs ). Subsequently, EVs and EVs were used in LB*-DG LB-DG LB*-DG spike-in experiments. Both EVs and EVs , were spiked into sterile LB, sterile LB supplemented LB-DG LB*-DG with external SMase, or sterile LB containing both external SMase and Imipramine, and the results were compared to those from spike-in experiments with EVs and EVs (Supplementary Fig. 8a).\nLB LB*\nIrrespec>ve of the method used for B. cereus EV prepara>on, EV degrada>on was observed exclusively in the presence of SMase and was inhibited by Imipramine. No significant differences were observed in the extent of SMase-mediated EV degrada>on between EVs , EVs , EVs , and EVs LB LB* LB-DG LB*- (Supplementary Fig. 8a). Furthermore, EVs purified by density gradient centrifuga>on were tested DG posi>ve for sphingomyelins (Supplementary Fig. 8b). Similar amounts of sphingomyelin were observed in EVs , EVs , EVs , and EVs . These findings demonstrate that density gradient- LB-DG LB*-DG LB LB* purified B. cereus EVs have the same sphingomyelin-posi>ve lipid architecture and SMase suscep>bility as crudely purified B. cereus EVs (Supplementary Fig. 8a, b).\n17\n3.2. Regarding the claim ‘it is possible that the majority of EVs in this condi<on [LB] is yeast derived EVs with bacterial MVs being a minor popula<on’:\nBased on our addi>onal experiments and data analyses, we think that this can be ruled out for the following reasons:\n1. Results from electron microscopic analysis: Sterile LB was analysed by electron microscopy. No EV structures were observed (see new Supplementary Fig. 2e), indica>ng that the yeast-extract- derived EVs from LB media are not a significant cons>tuent of our EVs prepara>on.\nLB\n2. Results from NTA (see revised Fig. 1b): We subjected sterile LB to ultracentrifuga>on and then analysed the poten>ally pelleted par>cles by NTA. No pelletable par>cles were detectable, demonstra>ng that yeast-extract-derived EVs from LB are not significant cons>tuents of our bacterial EVs . Furthermore, immediately a`er inocula>ng LB with B. cereus, no EVs were LB detectable, but a marked increase in the EV yields occurred during the ini>al 6 h of incuba>on (see revised Fig 1b). These results show that B. cereus ac>vely produces EVs in LB during the early growth phase.\n3. Results from our EV proteome analysis: We assessed the presence of yeast proteins in our EV proteomics data by performing a database search against both the Bacillus cereus (proteome ID UP000002214) and the Saccharomyces cerevisiae (strain ATCC 204508/S288c; reference proteome ID UP000002311) protein database.\nThis analysis revealed a negligible background of yeast-proteins, with a mean contribu>on of 0.16 % across all replicates, while 99.84 % of the proteins were assigned to B. cereus (Explanatory Fig. 3). To sta>s>cally validate it, a paired t-test was performed on the log -transformed data, yielding a very 10 significant p-value of p = 9.93 × 10-6. This p-value confirms that the yeast can be considered as background noise. It is mathema>cally improbable for a trace 0.16 % protein frac>on to drive this high level of observed EV degrada>on and sphingolipid remodelling.\nExplanatory Fig. 3: Analysis of the proteome data of EVs .\nLB\nThe contribu>on of yeast proteins to the EV-proteome data\nfrom EVsLB isolated from B. cereus cultures grown in LB,\nwas inves>gated. Therefore, the mass spectrometric\nintensi>es (iBAQ values) of all proteins matching S.\ncerevisiae were summed and divided by the total protein\nintensity per sample to determine the contribu>on of yeast-\nderived proteins to the EVs proteome. The same\nLB\nprocedure was performed on B. cereus proteins.\nLines 95-104: In addi>on, we employed two complementary transmission electron microscopy (TEM) approaches: (i) imaging of ultrathin sec>ons prepared from resin-embedded B. cereus EVs that were subsequently stained (Supplementary Fig. 2a, b), and (ii) the drop-on-grid method, in which B. cereus EVs were directly dropped onto TEM grids (Supplementary Fig. 2c, d). The TEM analyses confirmed that B. cereus EVs deriving from both media are lipid-bilayer bordered en>>es that are sphere- shaped. In the sterile media (LB, MOD) controls, no par>cle-like structures were detected by TEM (Supplementary Fig. 2e, f).\nLines 79-91: To inves>gate how nutrient complexity affects EV secre>on in Gram-posi>ve bacteria, we compared B. cereus EV yields from complex, nutrient-rich (LB) and defined, nutrient-scarce (MOD) media over >me. The eme>c B. cereus reference strain F4810/72, which served as a model organism, was grown either in LB or in MOD. EVs were isolated from bacterial cultures a`er 0 h, 3 h, 6 h, 9 h, 12 h and 15 h by differen>al centrifuga>on followed by ultracentrifuga>on, as outlined in figure 1a (Fig. 1a). The EVs isolated from B. cereus cultures were designated as EVs or EVs , respec>vely. LB MOD Immediately a`er inocula>ng LB and MOD with B. cereus, as well as in sterile media controls, no EVs were detectable (Fig. 1b). However, a marked increase in the B. cereus EV yields occurred during the ini>al 6 h of cul>va>on. Specifically, a 70-fold increase in EV yields was observed between 3 h and 6 h in both LB and MOD, resul>ng in comparable EV yields of EVs and EVs at 6 h. LB MOD Unexpectedly, EV yields decreased significantly a`er 9 h in LB but remained stable in MOD (Fig. 1b). This decrease might either reflect a different stability of EVs and EVs or might be linked to dis>nc>ve factors ac>vely LB MOD degrading EVs .\nLB\n4. The authors should analyze LB medium without bacterial inocula<on and examine the \"MV frac<on\" from this control. This would help determine whether the observed effects are due to bacterial MVs or to yeast extract–derived EVs, or free sphingolipids present in the medium.\nAuthor response: We thank the reviewer for sugges>ng the incorpora>on of this nega>ve control.\nAs suggested, we have analysed the “MV frac>on” in LB medium. To do so, we subjected sterile LB to ultracentrifuga>on and then analysed the poten>ally pelleted par>cles (“MV frac>on”) by NTA. No pelletable par>cles were detected in LB medium by our protocol (see also response claim 3 above).\nThe results of the ultracentrifuged “MV frac>on” control from sterile LB and MOD media are now included in the revised Fig. 1b and the results sec>on (Lines 84-88).\nTo further validate the absence of EVs stemming from LB, TEM images of LB were obtained using the drop-on-grid method (new Supplementary Fig. 2e). No EV-like structures were observed, confirming the absence of yeast extract-derived EVs in LB medium used in our study.\nIn summary, these results confirm that the observed effects in our experiments are aaributable to bacterial EVs, not to components of the LB medium.\nThe respec>ve sec>ons in the manuscript now read as follows:\nLines 84-88: Immediately a`er inocula>ng LB and MOD with B. cereus, as well as in sterile media controls, no EVs were detectable (Fig. 1b). However, a marked increase in the EV yields occurred during the ini>al 6 h of incuba>on. Specifically, a 70-fold increase in EV yields was observed between 3 h and 6 h in both LB and MOD, resul>ng in comparable EV yields of EVs and EVs at 6 h. LB MOD\nLines 95-104: In addi>on, we employed two complementary transmission electron microscopy (TEM) approaches: (i) imaging of ultrathin sec>ons prepared from resin-embedded B. cereus EVs that were subsequently stained (Supplementary Fig. 2a, b), and (ii) the drop-on-grid method, in which B. cereus EVs were directly dropped onto TEM grids (Supplementary Fig. 2c, d). The TEM analyses confirmed that B. cereus EVs deriving from both media are lipid-bilayer bordered en>>es that are sphere- shaped. In the sterile media (LB, MOD) controls, no par>cle-like structures were detected by TEM (Supplementary Fig. 2e, f).\n5. If bacterial MVs are involved and the strain do not produce sphingolipids, the overall data is sugges<ng that the MV lipid composi<on can be altered by extracellular lipid but is not well inves<gated. The authors should examine whether sphingolipid can be incorporated in MVs (or if bacterial MVs become associated with yeast EVs).\nAuthor response: We thank the reviewer for this insigh~ul comment. We concur that the influence of extracellular lipids on bacterial EV lipid composi>on remains poorly explored, and our study provides ini>al evidence that nutrient complexity shapes EV lipid architecture. Since B. cereus cannot synthesise sphingolipids, our findings suggest that medium-derived sphingomyelin can be taken up by B. cereus and subsequently incorporated into EV membranes.\nTo further experimentally support this idea, we grew B. cereus cultures in LB supplemented with fluorescently labelled sphingomyelin (SM C11; C11 TopFluor™ Sphingomyelin). A`er 6 h of cul>va>on, we isolated EVs via differen>al ultracentrifuga>on. Fluorescence microscopy revealed membrane-associated fluorescence in B. cereus, indica>ng uptake and incorpora>on of the exogenous supplemented SM C11 in B. cereus cell membranes (Explanatory Fig. 4a). Moreover, fluorescence measurements of the isolated B. cereus EVs (B. cereus+SM C11 EVs) showed that SM C11 is indeed incorporated in B. cereus EVs (see for details Explanatory Fig. 4b). The signal of the controls (EVs from 20 unlabelled B. cereus cultures (B. cereus-SM C11 EVs), sterile LB spiked with SM C11 (LB+SM C11 Control)) did not exceed the background signal obtained for sterile LB (LB-SM C11 Control).\nExplanatory Fig. 4. Sphingomyelin presented in the culture media are scavenged by B. cereus and incorporated into B. cereus EVs. a Bacteria were grown in LB, supplemented with 4 µM of C11 TopFluor™ Sphingomyelin (SM C11) solved in DMSO (upper panel). An equal amount of DMSO was added to the no-treatment control (lower panel). Ager 6 h of cul>va>on in the presence of SM C11 or DMSO, the bacterial cells were harvested by centrifuga>on and washed 3 >mes to remove any unbound dye. The final bacterial pellet was resuspended in PBS, applied on a cover slip, dried and covered using moun>ng media. Subsequently, cover slips were inves>gated by means of an inverted widefield microscope (Observer Z1, Zeiss) using phase contrast and an appropriate filter (excita>on: 450-490 nm; emission: 515-565 nm). b EVs produced by B. cereus grown in LB plus SM C11 (B. cereus+SM C11 EVs) as well as in LB plus DMSO (B. cereus-SM C11 EVs) were isolated by ultracentrifuga>on, washed two >mes and the fluorescence intensi>es (excita>on: 490 nm; emission: 530 nm) were analysed using a fluorescence micro>ter plate reader (Spark® Mul>mode Microplate Reader, TECAN). Sterile media spiked with DMSO-solved SM (LB+SM C11 Control) was included to check for poten>al pelletable SM C11 aggregates. Sterile media supplemented with DMSO (LB-SM C11 Control) served as nega>ve control.\nFurthermore, as yeast EVs could not be detected or isolated in the LB medium (see also responses to claims 3 and 4 above, revised Fig. 1b, newly added Supplementary Fig. 2e), it can be assumed that bacterial EVs do not become associated with yeast-extract-derived EVs (origina>ng from LB media) in our experimental se(cid:127)ng. This no>on is supported by our EV proteome analyses, which revealed that less than 0.2 % of identified proteins matched yeast proteins, confirming a minimal contribution of yeast-derived components to our EV preparations (see also response to claim 3.2 and Explanatory Fig. 3).\n6. Related to the point above the authors indicate in Fig. 7 and elsewhere that the MVs derived from LB consist of sphingolipids and other lipids. If the EV mainly consist of sphingolipids, it could be degraded but if sphingolipid is not a major component, I guess the par<cle may remain intact. I fully understand it is 21 challenging to see the lipid composi<on in a single par<cle but the heterogeneity of EVs should be taken into considera<on.\nAuthor response: We agree with the reviewer that EV heterogeneity may affect EV degrada>on. So far, bacterial EV heterogeneity has been demonstrated mainly based on morphology (DOI: 10.3389/fmicb.2021.713669; DOI: 10.1128/Spectrum.01273-21). However, it is conceivable that the distribu>on of single lipid species among EVs is also heterogeneous. Such lipid heterogeneity may indeed influence suscep>bility to SMase-mediated degrada>on. In our experiments, bulk measurements showed a steep decrease, but not complete loss, of EVs upon SMase treatment (Fig. LB 1b, h, j, Fig. 4b, d, f, g). Yet it remains to be elucidated whether this is attributable to SMase exhaustion or to the presence of a resistant subpopula>on of EVs .\nLB\nWe agree that resolving and deciphering EV lipid heterogeneity will be pivotal for understanding EV biology in the forthcoming years, but this is clearly beyond the scope of the current study, which focuses on a novel role of EVs as a nutrient resource. Thus, the following statement was incorporated into the discussion:\nLines 445-459: Therefore, further insight into bacterial EV heterogeneity and the distribu>on of lipid species within EV popula>ons is needed. While bacterial EV heterogeneity has so far been demonstrated mainly at the morphological level62,63, it is plausible that different EV morphologies result from dis>nct EV lipid architectures, reflec>ng differences in membrane origin, curvature, or biogenesis pathways54,64,65. Resolving EV lipid composi>on at the single-par>cle level will be crucial for determining whether all EV subtypes are equally suscep>ble to SMase-mediated degrada>on and for understanding how EV stability is regulated across heterogeneous popula>ons. Emerging single- vesicle analy>cal approaches, such as direct stochas>c op>cal reconstruc>on microscopy (dSTORM), Raman trapping analysis and single EV flow cytometry, allow analysing single EVs in eukaryo>c systems66–68, but their applicability remains very limited for bacterial EVs due to the absence of specific marker proteins and the high diversity of bacterial species69. Adap>ng and extending these technologies to bacteria will be essen>al to determine how bacterial communi>es u>lise EV heterogeneity to fine-tune EV stability, cargo delivery and resource alloca>on, thereby offering further mechanis>c insights into SMase-mediated EV degrada>on.\n7. It is unclear how the MVs were quan<fied, for example in fig. 1b. were the MVs first isolated and then counted? If only crude precipita<on was used without further purifica<on, other par<cles such as flagella could be present and might be included in the NTA counts. This should be clarified.\nAuthor response: We apologise for not sta>ng this more clearly and have reworked the sec>on.\nEVs were isolated by differen>al ultracentrifuga>on, and the EV yields were determined by NTA. A more detailed descrip>on is now given in the legend of Fig. 1b, which now reads as follows:\nSince > 99 % of the par>cles detected by NTA in our EV prepara>ons, isolated using the ultracentrifuga>on-based protocol, were below 400 nm, it can be assumed that larger par>cles, such as flagella, did not cons>tute a significant component of the NTA counts (Explanatory Fig. 5a, b).\nExplanatory Fig. 5. Extended size distribuMon analysis of EVs. Size distribu>ons of (a) EVs and (b) EVs LB MOD shown over 0-2000 nm demonstrate absence of larger par>cle structures beyond the EV size range (< 400 nm).\n8. It is beger to show TEM image of a wider view rather than showing one image of a par<cle. From the image provided it is hard to tell if they are EV or not. Beger images might be obtained if ultrathin sec<ons are not used.\nAuthor response: We appreciate the reviewer's sugges>on and performed addi>onal TEM analyses employing the drop-on-grid method. Representa>ve images of EVs and EVs , obtained by means LB MOD of the drop-on-grid method, are presented in new Supplementary Fig. 2c, d, together with the corresponding nega>ve controls from the sterile media (see new Supplementary Fig. 2e, f).\nThe respec>ve sec>on in the manuscript now read as follows:\nLines 95-104: In addi>on, we employed two complementary transmission electron microscopy (TEM) approaches: (i) imaging of ultrathin sec>ons prepared from resin-embedded B. cereus EVs that were subsequently stained (Supplementary Fig. 2a, b), and (ii) the drop-on-grid method, in which B. cereus 23 EVs were directly dropped onto TEM grids (Supplementary Fig. 2c, d). The TEM analyses confirmed that B. cereus EVs deriving from both media are lipid-bilayer bordered en>>es that are sphere- shaped. In the sterile media (LB, MOD) controls, no par>cle-like structures were detected by TEM (Supplementary Fig. 2e, f).\n24"}, {"round": 2, "reviewer_comments": {"reviewer_2": "The authors did an excellent job addressing the concerns. The revised manuscript is clearer, and the additional experiments demonstrate how incorporation of sphingolipids can alter the fate of MVs, which is important for understanding MV function and turnover.\nI do not have any further comments."}, "author_response": ""}]

Decision letter