Released bacterial ATP shapes local and systemic inflammation during abdominal sepsis

Daniel Spari; Annina Schmid; Daniel Sanchez-Taltavull; Shaira Murugan; Keely Keller; Nadia Ennaciri; Lilian Salm; Deborah Stroka; Guido Beldi

doi:10.7554/eLife.96678

. 2024 Aug 20;13:RP96678. doi: 10.7554/eLife.96678

Released bacterial ATP shapes local and systemic inflammation during abdominal sepsis

Daniel Spari ^1,², Annina Schmid ^1,², Daniel Sanchez-Taltavull ^1,², Shaira Murugan ^1,², Keely Keller ^1,², Nadia Ennaciri ^1,², Lilian Salm ^1,², Deborah Stroka ^1,², Guido Beldi ^1,^2,^✉

Editors: Kiyoshi Takeda³, Wendy S Garrett⁴

PMCID: PMC11335348 PMID: 39163101

Abstract

Sepsis causes millions of deaths per year worldwide and is a current global health priority declared by the WHO. Sepsis-related deaths are a result of dysregulated inflammatory immune responses indicating the need to develop strategies to target inflammation. An important mediator of inflammation is extracellular adenosine triphosphate (ATP) that is released by inflamed host cells and tissues, and also by bacteria in a strain-specific and growth-dependent manner. Here, we investigated the mechanisms by which bacteria release ATP. Using genetic mutant strains of Escherichia coli (E. coli), we demonstrate that ATP release is dependent on ATP synthase within the inner bacterial membrane. In addition, impaired integrity of the outer bacterial membrane notably contributes to ATP release and is associated with bacterial death. In a mouse model of abdominal sepsis, local effects of bacterial ATP were analyzed using a transformed E. coli bearing an arabinose-inducible periplasmic apyrase hydrolyzing ATP to be released. Abrogating bacterial ATP release shows that bacterial ATP suppresses local immune responses, resulting in reduced neutrophil counts and impaired survival. In addition, bacterial ATP has systemic effects via its transport in outer membrane vesicles (OMV). ATP-loaded OMV are quickly distributed throughout the body and upregulated expression of genes activating degranulation in neutrophils, potentially contributing to the exacerbation of sepsis severity. This study reveals mechanisms of bacterial ATP release and its local and systemic roles in sepsis pathogenesis.

Research organism: E. coli, Mouse

eLife digest

Sepsis is a severe condition often caused by the body’s immune system overreacting to bacterial infections. This can lead to excessive inflammation which damages organs and requires urgent medical care. With sepsis claiming millions of lives each year, new and improved ways to treat this condition are urgently needed. One potential strategy for treating sepsis is to target the underlying mechanisms controlling inflammation.

Inflamed and dying cells release molecules called ATP (the energy carrier of all living cells), which strongly influence the immune system, including during sepsis. In the early stages of an infection, ATP acts as a danger signal warning the body that something is wrong. However, over time, it can worsen infections by disturbing the immune response.

Similar to human cells, bacteria release their own ATP, which can have different impacts depending on the type of bacteria and where they are located in the body. However, it is not well understood how bacterial ATP influences severe infections like sepsis.

To investigate this question, Spari et al analysed how ATP is released from Escherichia coli, a type of bacteria that causes severe infections. This revealed that the bacteria secrete ATP directly in to their environment and via small membrane-bound structures called vesicles.

Spari et al. then probed a mouse model of abdominal sepsis which had been infected with E. coli that release either normal or low levels of ATP. They found that the ATP released from E. coli impaired the mice’s survival and lowered the number of neutrophils (immune cells which are important for defending against bacteria) at the site of the infection. The ATP secreted via vesicles also altered the role of neutrophils but in more distant regions, and it is possible that these changes may be contributing to the severity of sepsis.

These findings provide a better understanding of how ATP released from bacteria impacts the immune system during sepsis. While further investigation is needed, these findings may offer new therapeutic targets for treating sepsis.

Introduction

Worldwide, 11 million sepsis-related deaths were reported in 2017, which accounted for an estimated 19.7% of all global deaths (Rudd et al., 2020). Given its high incidence and immense socio-economic burden, the World Health Organization (WHO) has declared sepsis as a global health priority (Reinhart et al., 2017).

Sepsis is defined as life-threatening organ dysfunction caused by an imbalanced host immune response to infection. Antibiotic treatment remains the main approach to treat sepsis; however, despite the use of broad-spectrum antibiotics, lethality remains high. Immune-modulating strategies are an additional approach to antibiotics to curb excessive inflammation and to support an effective defense against the infectious agents. Until recently however, most trials inhibiting cytokine responses or Toll-like receptors failed, indicating that alternative approaches for immunomodulation are required (Cao et al., 2023).

It has been shown that adenosine triphosphate (ATP), as soon as it is released into the extracellular space, critically modulates inflammatory and immune responses (Di Virgilio et al., 2020; Eltzschig et al., 2012) by activating ionotropic P2X and metabotropic P2Y receptors (Burnstock, 2020; Junger, 2011). Also, such purinergic signaling critically alters immune responses during sepsis (Dosch et al., 2019; Ledderose et al., 2016; Spari and Beldi, 2020). In particular, we have described that the connexin-dependent release of ATP by macrophages initiates an autocrine loop of over-activation, resulting in altered local and systemic cytokine secretion, which exacerbates abdominal sepsis (Dosch et al., 2019). Such sepsis-promoting effects of host-derived extracellular ATP are secondary to inflammation initiated by bacterial pathogens.

Recently, it has been discovered that also bacteria release ATP into the extracellular space (Mempin et al., 2013). Such ATP release might be a conserved mechanism of protection from host defense and precede host responses. ATP release has been shown for a variety of bacteria including the sepsis-associated Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) from the Proteobacteria phylum or Enterococcus faecalis (E. faecalis) and Staphylococcus aureus (S. aureus) from the Firmicutes phylum (Diekema et al., 2019; Hironaka et al., 2013; Iwase et al., 2010; Mempin et al., 2013; Mureșan et al., 2018).

The mechanisms by which inflammatory and immune responses in the host are modulated by such released bacterial ATP have just begun to be elucidated (Spari and Beldi, 2020). In colonized compartments such as the intestine, it has been shown that ATP released by mutualistic bacteria modulates local cellular and secretory immune responses (Atarashi et al., 2008; Perruzza et al., 2017; Proietti et al., 2019) and in the mouth, bacterial ATP release leads to biofilm dispersal and periodontitis (Ding et al., 2016a; Ding and Tan, 2016b). However, the role of ATP released by bacteria invading non-colonized compartments, such as the abdominal cavity or the blood in the context of local and systemic infections, remains to be determined.

In this study, we investigated if ATP released from bacteria influences the outcome of abdominal sepsis. We first isolated sepsis-associated bacteria and measured the amount of ATP they release. Second, we analyzed the function of the inner bacterial membrane on ATP release over time in E. coli and in E. coli with mutations in integral respiratory chain proteins (Mempin et al., 2013). Third, the function of the outer bacterial membrane on ATP release during growth was assessed using porin mutants (Alvarez et al., 2017; Choi and Lee, 2019). Fourth, we investigated local effects of ATP in the abdominal cavity. Lastly, based on the finding that bacteria secrete outer membrane vesicles (OMV) (Schwechheimer and Kuehn, 2015), we investigated systemic consequences of released bacterial ATP.

Results

E. coli, one of the major pathogens in sepsis, releases ATP in a growth-dependent manner

To assess ATP release of sepsis-associated bacteria, abdominal fluid of patients with abdominal sepsis was sampled and an/aerobically incubated on LB agar plates (Figure 1A). Twenty-five different colonies were randomly picked and analyzed by whole 16S-rRNA Sanger sequencing, which resulted in 12 different bacterial species (Figure 1B). From these, the four most clinically important sepsis-associated bacteria E. coli, K. pneumoniae (both gram^neg), E. faecalis, and S. aureus (both gram^pos) (Diekema et al., 2019; Mureșan et al., 2018) were further cultivated for experimental studies. We quantified released ATP over time (Figure 1—figure supplement 1) using a luciferin-luciferase-based assay. A growth-dependent release of ATP was observed in all species, peaking during exponential growth phase (Figure 1C). Cumulative amount of released ATP was quantified using the area under the curve (AUC) of released ATP over time (AUC ATP). ATP release was detected across all assessed species (Figure 1D). To model these findings in mice, abdominal sepsis was induced using a standardized cecal ligation and puncture (CLP) model (Dosch et al., 2019; Figure 1E). Similar to human samples, Proteobacteria and Firmicutes phyla were predominating (Figure 1F, see Figure 1B). In the mouse model, E. coli released notably more cumulative ATP compared to E. faecalis and S. aureus (Figure 1G and H). The bacterial species assessed in humans and mice (E. coli, E. faecalis, S. aureus) differed on the strain level (sequences deposited, see Data availability statement) confirming that ATP release is strain-specific (Mempin et al., 2013). In summary, sepsis-associated bacteria release ATP in a growth-dependent and strain-specific manner. E. coli, which is one of the most frequent facultative pathogens in patients with abdominal sepsis, released the highest amount of ATP isolated from a standardized mouse model of abdominal sepsis.

Figure 1. — (A) Experimental approach to isolate and cultivate sepsis-associated bacteria from abdominal fluid of patients with abdominal sepsis. (B) Bacterial species identified by whole 16S-rRNA Sanger sequencing from abdominal fluid of patients with abdominal sepsis. Three colonies out of 25 could not be identified. (C) Measurement of released ATP (M) and growth (OD₆₀₀) over time (hours) from the four sepsis-associated bacteria *E. coli*, *K. pneumoniae*, *E. faecalis,* and *S. aureus* isolated from patients. N=2 independent bacteria cultures. Means and standard deviations are shown. (D) Area under the curve (AUC) of released ATP over time (M*hours) of the previously assessed bacteria (cumulative ATP). One-way ANOVA, N=2 independent bacteria cultures. Means and individual values are shown. (E) Experimental approach to isolate and cultivate sepsis-associated bacteria from abdominal fluid of mice with abdominal sepsis. (F) Bacterial species identified by whole 16S-rRNA Sanger sequencing from abdominal fluid of mice with abdominal sepsis. Seven colonies out of 25 could not be identified. (G) Measurement of released ATP (M) and growth (OD₆₀₀) over time (hours) from the three sepsis-associated bacteria *E. coli*, *E. faecalis,* and *S. aureus* isolated from mice. N=2 independent bacteria cultures. Means and standard deviations are shown. (H) AUC of released ATP over time (M*hours) of the previously assessed bacteria (cumulative ATP). One-way ANOVA, N=2 independent bacteria cultures. Means and individual values are shown.

Figure 1—figure supplement 1. — (A) Experimental approach to isolate and cultivate sepsis-associated bacteria from abdominal fluid of patients with abdominal sepsis. (B) Bacterial species identified by whole 16S-rRNA Sanger sequencing from abdominal fluid of patients with abdominal sepsis. Three colonies out of 25 could not be identified. (C) Measurement of released ATP (M) and growth (OD₆₀₀) over time (hours) from the four sepsis-associated bacteria *E. coli*, *K. pneumoniae*, *E. faecalis,* and *S. aureus* isolated from patients. N=2 independent bacteria cultures. Means and standard deviations are shown. (D) Area under the curve (AUC) of released ATP over time (M*hours) of the previously assessed bacteria (cumulative ATP). One-way ANOVA, N=2 independent bacteria cultures. Means and individual values are shown. (E) Experimental approach to isolate and cultivate sepsis-associated bacteria from abdominal fluid of mice with abdominal sepsis. (F) Bacterial species identified by whole 16S-rRNA Sanger sequencing from abdominal fluid of mice with abdominal sepsis. Seven colonies out of 25 could not be identified. (G) Measurement of released ATP (M) and growth (OD₆₀₀) over time (hours) from the three sepsis-associated bacteria *E. coli*, *E. faecalis,* and *S. aureus* isolated from mice. N=2 independent bacteria cultures. Means and standard deviations are shown. (H) AUC of released ATP over time (M*hours) of the previously assessed bacteria (cumulative ATP). One-way ANOVA, N=2 independent bacteria cultures. Means and individual values are shown.

Bacterial ATP release is dependent on ATP synthesis at the inner bacterial membrane and correlates with bacterial growth

After having demonstrated that sepsis-associated bacteria release ATP, we next questioned whether and how ATP release is dependent on ATP generation. ATP synthase and cytochrome oxidases, which are located in the inner bacterial membrane, are key components of ATP generation under aerobic conditions. Therefore, ATP release of the E. coli parental strain (PS) was compared to all available mutants of ATP synthase subunits (ΔatpA, ΔatpB, ΔatpC, ΔatpD, ΔatpE, ΔatpF, ΔatpH) and cytochrome bo₃ oxidase subunits (ΔcyoA, ΔcyoB, ΔcyoC, ΔcyoD) from the Keio collection (Baba et al., 2006; Yamamoto et al., 2009). The use of different mutants allows to identify the most relevant subunits influencing ATP release. Also, it allows to identify a possible correlation of bacterial ATP release with growth, which is a function of ATP generation (Figure 2A; Galber et al., 2021; Ihssen et al., 2021; Ivancic et al., 2008; Lundin, 2000).

Figure 2—figure supplement 1. — (A) Illustration depicting the location of ATP synthase and cytochrome *bo₃* oxidase in gram^neg bacteria. (B) Measurement of released ATP (M) and growth (OD₆₀₀) over time (hours) from cytochrome *bo₃* oxidase (cyo) and ATP synthase (atp) mutants. The parental strain (PS) was added as a control. N=2 independent bacteria cultures. Means and standard deviations are shown. (C) Area under the curve (AUC) of released ATP over time (M*hours) of the previously assessed bacteria (cumulative ATP) is shown individually in the left panel. N=2 independent bacteria cultures. Means and individual values are shown. Means of grouped cyo and atp mutants are compared in the right panel. t-Test. Means and individual values are shown. (D) Cumulative ATP (M*hours) and cumulative growth (OD₆₀₀*hours) of all assessed cyo and atp mutants and the PS were plotted against each other. Pearson’s correlation (r) and coefficient of determination (R²) of the applied linear model are depicted. 95% confidence level is shown by the black dashed lines.

© 2024, BioRender Inc

Figure 2A was created using BioRender, and is published under a CC BY-NC-ND 4.0. Further reproductions must adhere to the terms of this license

Bacterial growth (OD₆₀₀) and ATP release were measured over time and cumulative ATP release (AUC ATP) was assessed (Figure 2B). We first noticed that mutations in subunits of ATP synthase, which is the key enzyme of ATP generation, were generally associated with significantly lower cumulative ATP release compared to mutations in cytochrome bo₃ oxidase subunits (Figure 2C). Therefore, we suspected an interrelation between ATP generation and released ATP (see growth and ATP release curves in Figure 2B). We determined cumulative growth (AUC growth) in addition to cumulative ATP release and indeed, cumulative ATP release and cumulative growth were positively correlated (Figure 2D), similar to peak ATP and peak growth (OD₆₀₀) that are positively correlated (Figure 2—figure supplement 1). In summary, ATP release is directly dependent on ATP generation at the inner bacterial membrane. Mutations in subunits of bacterial ATP synthase have a higher impact on ATP generation, growth, and ATP release than mutations in subunits of cytochrome bo₃ oxidase (Figure 2C).

Outer bacterial membrane integrity and bacterial death determine bacterial ATP release during growth

We next focused on the outer membrane by challenging its integrity while leaving ATP generation and the inner membrane intact. For that purpose, we used the E. coli porin mutants ΔompC, ΔompF, ΔlamB, and ΔphoE (Figure 3A; Baba et al., 2006; Yamamoto et al., 2009), which have been shown to suffer from impaired outer membrane integrity in varying degrees (Choi and Lee, 2019). ATP release and growth were measured over time including E. coli PS as baseline and membrane destabilizing EDTA and stabilizing Ca²⁺ as additional controls (Leive, 1968). Cumulative ATP release (AUC ATP) from the porin mutants were notably different compared to the PS, being lowest in ΔompC and highest in ΔompF (Figure 3B and C).

Interestingly, the ΔompF mutant had also a very high peak of released ATP (Figure 3B). We hypothesized that this is because of impaired membrane integrity, resulting in ATP release during growth and potentially bacterial death. Thus, we focused on the individual ATP peaks during growth, which were observed after 4 hr of culturing. There was a strong negative correlation between the individual peak of released ATP (marked by the red line in Figure 3B) and growth at the same time point (Figure 3D).

We did not interfere with ATP generation at the inner membrane but deliberately challenged the outer membrane and tested therewith if destabilization of the outer membrane integrity is associated with bacterial death. Indeed, outer membrane integrity and bacterial death are significantly increased in ΔompF compared to ΔompC and the PS after 4 hr (ATP peak) of culturing (Figure 3E and F), akin to the amount of released ATP (Figure 3G). We conclude from these data that destabilization of the outer bacterial membrane (as observed with the ΔompF mutant) results in bacterial death that is associated with ATP release.

In summary, outer membrane integrity and finally bacterial death notably contribute to the amount of bacterial ATP release during growth.

Released bacterial ATP reduces neutrophil counts and impairs survival during abdominal sepsis

Next, we wanted to investigate the function of bacterial ATP release in vivo. To study this, we transformed the E. coli PS with an arabinose-inducible apyrase (PS+pAPY) and compared it to the PS transformed with the empty vector (PS+pEMPTY) (Proietti et al., 2019). In this model, ATP released by bacteria is hydrolyzed and consequently depleted by a periplasmic apyrase (Santapaola et al., 2006; Scribano et al., 2014).

Indeed, apyrase induction resulted in a significant reduction of ATP release in PS+pAPY, compared to PS+pEMPTY (Figure 4—figure supplement 1A and B). To test the consequences in vivo, apyrase was induced by arabinose 3 hr before intraabdominal (i.a.) injection into wild type C57Bl/6 mice (Figure 4A). Thereby ATP release was abrogated in the bacteria cultures that were used for injection (Figure 4B). In vivo, no difference in ATP levels was detected when ATP was measured directly in the abdominal fluid after 4 (Figure 4C) and 8 hr (Figure 4—figure supplement 1C). This is not surprising given that ATP is rapidly hydrolyzed by ectonucleotidases in vivo (Eltzschig et al., 2012). After both 4 (Figure 4D and E) and 8 hr (Figure 4—figure supplement 1D and E), no differences in local or systemic bacterial counts were observed. Yet, despite similar bacterial counts, the survival was significantly higher in the absence of bacterial ATP (PS+pAPY) compared to ATP-generating controls (PS+pEMPTY) after i.a. injection (Figure 4F).

Next, we asked how this difference in bacterial ATP release affects the immune system. Therefore, inflammatory cells in the abdominal cavity were characterized using flow cytometry (Figure 4G). As expected, a disappearance reaction of large peritoneal macrophages (LPM) was observed after both, E. coli PS+pEMPTY and E. coli PS+pAPY, i.a. injection compared to sham controls after 4 (Figure 4H) and 8 hr (Figure 4—figure supplement 1F; Ghosn et al., 2010). Such LPM disappearance following abdominal E. coli infection is a result of free-floating clots composed of LPM and neutrophils and important for effective pathogen clearance (Salm et al., 2023; Vega-Pérez et al., 2021; Zindel et al., 2021) but not dependent on ATP release according to our data. Interestingly, however, the number of small peritoneal macrophages (SPM) and CX3CR1^pos monocytes was significantly reduced, whereas neutrophils were significantly increased almost up to 8 hr (Figure 4I, Figure 4—figure supplement 1G) in bacterial ATP-depleted abdominal sepsis (PS+pAPY). This effect is dependent on released bacterial ATP given that no differences in bacterial counts were observed (see Figure 4D and E, Figure 4—figure supplement 1D–E).

In summary, ATP released by bacteria suppresses abdominal inflammatory responses and worsened survival in a model of abdominal sepsis.

Establishing ATP-loaded OMV as a model system to assess the systemic relevance of bacterial ATP

ATP is rapidly metabolized in the extracellular space and therefore, the mode of action of released bacterial ATP is limited to the immediate cellular vicinity (Junger, 2011). However, the outcome of sepsis is not only dependent on local but also on systemic responses to microorganisms. Therefore, we hypothesized that bacterial ATP has systemic effects as protected cargo in OMV (Alvarez et al., 2017). OMV are small (20–300 nm) spherical particles that are released by both gram^neg and gram^pos bacteria (Schwechheimer and Kuehn, 2015). In gram^neg bacteria, they bulge off the outer membrane and disseminate throughout the body (Jang et al., 2015). They are equipped with typical bacterial surface features lacking the machinery for self-reproduction, and contain DNA, proteins, and metabolites (Baeza and Mercade, 2021; Bitto et al., 2017; Kulp and Kuehn, 2010; Lee et al., 2007). Therefore, OMV are suited as a systemic delivery system for bacterial ATP. Indeed, recently, ATP has been detected in OMV derived from pathogenic Neisseria gonorrhoeae, Pseudomonas aeruginosa PAO1, and Acinetobacter baumannii AB41 (Pérez-Cruz et al., 2015).

To assess the potential of OMV as ATP carriers, we compared the OMV production from several hypervesiculation E. coli mutants (ΔmlaE, ΔmlaA, ΔrfaD, ΔdegP, ΔrodZ, ΔnlpI, ΔtolB) (Figure 5A; McBroom et al., 2006). The ΔnlpI and ΔtolB strains showed a 20- and 30-fold increase of OMV when compared with the PS (Figure 5B). We then assessed ATP release and growth over time from ΔnlpI, ΔtolB, and the PS, to identify their individual peak of ATP release, and isolated OMV at their individual peak of ATP release and after 24 hr (Figure 5—figure supplement 1A). ATP was detected in OMV from all assessed strains at the individual peak of ATP release but only in minimal detectable levels after 24 hr (Figure 5C). The ΔtolB OMV isolated after 24 hr were then used as ATP-depleted vehicles. Density gradient ultracentrifugation showed that most ΔtolB OMV were of similar density and protein composition (Figure 5D, Figure 5—figure supplement 1B). They were equipped with outer membrane ompF but not cytoplasmic ftsZ (Figure 5D), indicating that they are outer membrane derived. In order to generate OMV with known and constant ATP concentrations, we used electroporation (EP) to load OMV with ATP while empty OMV (ΔtolB OMV harvested from 24 hr culture) served as ATP-depleted controls (Fu et al., 2020; Lennaárd et al., 2021). Before and after EP, the OMV size distribution was assessed by nanoparticle tracking analysis and morphology by electron microscopy (Figure 5E, Figure 5—figure supplement 1C). OMV were loaded with ATP (Figure 5F) and over time, the amount of ATP in OMV decreased, especially at physiological (37°C) temperature (Figure 5G) as opposed to 4°C (Figure 5—figure supplement 1D).

Figure 5. — (A) Illustration depicting the location of assessed proteins that lead to a hypervesiculation phenotype if knocked out in the gram^neg bacterium *E. coli*. (B) Relative amount of OMV compared to the parental strain (PS) isolated from growth cultures of the assessed hypervesiculation mutants after 5 hr (exponential growth phase) and O/N (stationary phase). n=2 measurements of N=3 independent bacteria cultures. Means and individual values are shown. (C) Absolute quantification of ATP in OMV isolated from growth cultures of the PS, *ΔnlpI* and *ΔtolB* at their individual peak of ATP release and after 24 hr. n=2 measurements of N=3 independent bacteria cultures. Means and individual values are shown. (D) Amount of protein (BCA assay) detected in different fractions after density gradient ultracentrifugation. n=2 measurements of the different fractions. 20 µl of *E. coli* growth culture and 20 µl of each fraction were then characterized by Coomassie blue staining and specific detection of outer membrane ompF and cytoplasmic ftsZ. (E) Characterization of OMV by nanoparticle tracking analysis (n=5 measurements per sample) and electron microscopy (representative image) before and after electroporation. (F) Absolute quantification of ATP in OMV, which were loaded using different strategies. Columns 2–5: different concentrations of ATP incubated for 1 hr at 37°C (passive filling). Columns 6–12: different voltages with fixed settings for resistance (100 Ω) and capacitance (50 µF). N=2–9 independent experiments. Means and standard deviations are shown. (G) Relative quantification of ATP in OMV over 24 hr at 37°C after electroporation (0 hr=100%). n=2 measurements of N=3 independent experiments. Means and individual values are shown.

© 2024, BioRender Inc

Figure 5A was created using BioRender, and is published under a CC BY-NC-ND 4.0. Further reproductions must adhere to the terms of this license

Figure 5—figure supplement 1. — (A) Illustration depicting the location of assessed proteins that lead to a hypervesiculation phenotype if knocked out in the gram^neg bacterium *E. coli*. (B) Relative amount of OMV compared to the parental strain (PS) isolated from growth cultures of the assessed hypervesiculation mutants after 5 hr (exponential growth phase) and O/N (stationary phase). n=2 measurements of N=3 independent bacteria cultures. Means and individual values are shown. (C) Absolute quantification of ATP in OMV isolated from growth cultures of the PS, *ΔnlpI* and *ΔtolB* at their individual peak of ATP release and after 24 hr. n=2 measurements of N=3 independent bacteria cultures. Means and individual values are shown. (D) Amount of protein (BCA assay) detected in different fractions after density gradient ultracentrifugation. n=2 measurements of the different fractions. 20 µl of *E. coli* growth culture and 20 µl of each fraction were then characterized by Coomassie blue staining and specific detection of outer membrane ompF and cytoplasmic ftsZ. (E) Characterization of OMV by nanoparticle tracking analysis (n=5 measurements per sample) and electron microscopy (representative image) before and after electroporation. (F) Absolute quantification of ATP in OMV, which were loaded using different strategies. Columns 2–5: different concentrations of ATP incubated for 1 hr at 37°C (passive filling). Columns 6–12: different voltages with fixed settings for resistance (100 Ω) and capacitance (50 µF). N=2–9 independent experiments. Means and standard deviations are shown. (G) Relative quantification of ATP in OMV over 24 hr at 37°C after electroporation (0 hr=100%). n=2 measurements of N=3 independent experiments. Means and individual values are shown.

© 2024, BioRender Inc

Figure 5A was created using BioRender, and is published under a CC BY-NC-ND 4.0. Further reproductions must adhere to the terms of this license

In summary, OMV contain ATP and release ATP at physiological temperatures. To use OMV as an ATP delivery system, empty OMV were loaded using EP.

OMV-derived bacterial ATP induces degranulation processes in neutrophils after lysosomal uptake

OMV are potent inducers of inflammation and sepsis (Park et al., 2010; Park et al., 2013), which travel throughout the body and are taken up by a variety of cells (Bittel et al., 2021; Kim et al., 2013; Lee et al., 2018). To tests the hypothesis that ATP within OMV mediates systemic effects of invasive bacteria, we injected ATP-loaded and empty OMV i.a. and investigated the resulting inflammation 1 hr after injection (Figure 6A).

In the abdominal fluid, uptake of DiI-stained OMV by leukocytes was independent of ATP cargo (Figure 6B, Figure 6—figure supplement 1) and all major cell populations with phagocytic ability (LPM, SPM, neutrophils) were highly positive for OMV (Figure 6—figure supplement 2A and B). LPM dramatically decreased, whereas neutrophils increased in response to OMV when compared to sham controls (Figure 6—figure supplement 2C).

Within 1 hr, the DiI-stained OMV were distributed throughout the body and mainly taken up by neutrophils, with remarkable differences between organs (Figure 6—figure supplement 3A and B, C). The highest ratio of OMV^pos neutrophils compared to all other OMV^pos cells was observed in the lung in an ATP-independent manner (Figure 6C). Intracellular fate of engulfed OMV is still a matter of discussion but one possibility is the degradation in the endolysosomal compartment (Bielaszewska et al., 2017; Juodeikis and Carding, 2022). We therefore injected DiI-stained OMV i.a. to assess to which membrane compartment OMV co-localize. A strong co-localization with the endolysosomal compartment of pulmonary neutrophils was identified (Figure 6D).

To determine what pathways OMV-derived bacterial ATP initiates in neutrophils after uptake into the endolysosomal compartment, pulmonary neutrophils were isolated (Figure 6—figure supplement 4) for RNA sequencing. Uptake of ATP-loaded OMV resulted in a significantly different transcriptional activity compared to empty OMV (Figure 6E): The strongest differences were found in lysosomal and neutrophil degranulation pathways (Figure 6F, Figure 6—figure supplement 5). In the lysosomal pathway, transcripts for proteins involved in autophagosome-lysosome fusion (Gabarap), endosome to lysosome transport (Hgsnat, Laptm5), or enzymatic cleavage (Capn1, Fuca1, Ctsb, Ctsd, Gba) were significantly higher expressed in response to ATP-loaded OMV when compared to empty OMV (Figure 6F and G). Furthermore, neutrophil degranulation was significantly increased in response to ATP-loaded OMV as indicated by increased expression of gene transcripts resulting in antibacterial activity (Lyz2, S100a8, Camp) or NETosis (Tlr2, Itgb2) (Figure 6F and H).

In summary, OMV are phagocytosed locally by major cell populations with phagocytic ability. Remotely, OMV were mainly taken up by neutrophils, where they co-localize with the endolysosomal compartment. Delivery of ATP by OMV resulted in an upregulation of lysosomal activation and neutrophil degranulation.

Discussion

In this study, we have demonstrated that ATP release is dependent on the respiratory chain located at the inner bacterial membrane. ATP synthase is most likely dominant compared to cytochrome bo₃ oxidase because of its non-redundant function for ATP generation and bacterial growth. Mutations in one of the cytochrome bo₃ oxidase subunits cyoA, cyoC, or cyoD could be compensated by another subunit. This is supported by lower ATP release in the cyoB mutant, which harbors all three prosthetic groups of the cytochrome bo₃ oxidase and is therefore indispensable for proper function (Tsubaki et al., 2000). Alternatively, deficiency in the bo₃-type oxidase could be partially compensated by bd-type oxidases (Borisov et al., 2011; Grauel et al., 2021).

Instability of the outer bacterial membrane as we have seen for the ΔompF mutant (Choi and Lee, 2019) is associated with bacterial death and ATP release. It remains unclear whether loss of ATP results directly in bacterial death or bacterial death is the direct result of impaired outer bacterial membrane stability and ATP release is secondary to bacterial death. However, since the inner membrane and ATP generation remains intact and the periplasmic space is considered generally devoid of ATP, the latter seems more likely (Kulp and Kuehn, 2010). Previous studies used Sytox/PI staining and microscopy to identify bacterial death and did not identify bacterial death as a relevant source of extracellular ATP during exponential growth (Hironaka et al., 2013). Conversely, we used flow cytometry, a quantitatively more sensitive method, and our data demonstrated that impaired membrane integrity and bacterial death are critical for ATP release during growth. Despite low rates of bacterial death during exponential growth (Koch, 1959), and a low ratio of dead to live bacteria, the high gradient between intra- and extracellular ATP (approximately 100–1000× higher) might be sufficient to explain the amount of released ATP measured (Leduc and van Heijenoort, 1980; Mempin et al., 2013).

ATP was detected within OMV and the concentration of ATP within OMV is sufficient to activate P2-type receptors in lysosomes (Araujo et al., 2020; Junger, 2011). Furthermore, OMV are released in response to environmental stresses like infection and sepsis (Kulp and Kuehn, 2010; Orench-Rivera and Kuehn, 2016). ATP is likely to activate P2 receptors, which have been shown to be expressed in lysosomes, such as P2X1, P2X3, or P2X4 (Qureshi et al., 2007; Robinson and Murrell-Lagnado, 2013). OMV can therefore be considered as non-living bacteria-resembling highly inflammatory vesicles (Jang et al., 2015; Kulp and Kuehn, 2010) that effectively distribute ATP throughout the body to activate cells, such as neutrophils, initiating systemic inflammatory responses. Activation of neutrophils in response to ATP-loaded OMV resulted in upregulation of inflammatory, lysosomal, and neutrophil degranulation pathways as well as an upregulation of the apoptosis pathway and genes involved in NETosis by a hitherto unknown mechanism. These pathways explain in part the low neutrophil counts we observed in mice. Such remote degranulation in response to OMV is unlikely to control bacteria at the source of sepsis but rather harmful to host tissues increasing sepsis severity (Eichelberger and Goldman, 2020).

The study has several limitations: Bacterial ATP release is strain specific (Figure 1; Mempin et al., 2013). As we focused on the laboratory BW25113 E. coli strain, it remains to be elucidated if impaired outer membrane integrity and bacterial death are also of such importance in other gram^neg or also gram^pos bacteria. The approach to load OMV with ATP is rather artificial; it is, however, the only way to assure that ATP-loaded and empty OMV only differ in their ATP cargo. OMV have surface antigens and contain DNA, proteins, and other metabolites (Kulp and Kuehn, 2010), which are known to elicit inflammation as well. This was controlled using the same OMV as baseline vehicles.

Several open questions need to be addressed in future projects: It remains to be determined how OMV are physiologically loaded with ATP. Potentially, despite the lack of a transporter, ATP may similarly to eukaryotic cells leak (Yegutkin et al., 2006) across the inner membrane into the periplasmic space that lacks the enzymes for ATP generation. Different types of OMV have been described in recent years, e.g., outer-inner membrane vesicles (O-IMV) or explosive OMV (Juodeikis and Carding, 2022; Takaki et al., 2020; Toyofuku et al., 2019; Turnbull et al., 2016; Turner et al., 2015), which are composed of outer membrane, inner membrane, and cytoplasmic content. The mechanisms, how these types of OMV are generated, could explain that ATP is found within them. However, the ΔtolB mutant produces, unlike other tol mutants, only very few O-IMV (0.1–2% of all OMV) (Pérez-Cruz et al., 2013; Reimer et al., 2021; Takaki et al., 2020) and our western blot analysis suggests that our OMV are primarily outer membrane derived. Future studies may address the ATP cargo of the different OMV subgroups.

OMV are promising diagnostic molecular biomarkers in gram^neg sepsis (Michel and Gaborski, 2022) and it would be of relevance to compare OMV isolated from septic and control patients to assess possible differences in ATP cargo. Furthermore, it remains to be elucidated, which mechanisms lead to low local neutrophil counts. Since ATP is involved in cell death (Proietti et al., 2019) as well as in chemotaxis (Junger, 2011), increased cell death, impaired infiltration, or a combination of both is possible.

This study reveals that ATP is released by bacteria during growth because of impaired membrane integrity and bacterial death. ATP is also being released via OMV and therefore acts locally (direct release) and systemically (via OMV). Bacterial ATP reduces neutrophil counts, activates the endolysosomal system, and upregulates neutrophil degranulation, which together increase the severity of abdominal infection and early sepsis. These findings have the potential to lead to the development of novel treatments for abdominal sepsis, e.g., by in vitro generated OMV that modulate neutrophil function via delivery of inhibitors to intracellular purinergic receptors during sepsis.

Materials and methods

Human data

From five patients that underwent revision laparotomy because of abdominal sepsis, swabs were taken from abdominal fluid, streaked on LB agar plates (15 g Agar, 5 g Bacto Yeast Extract, 10 g Bacto Tryptone, 5 g NaCl in 1 l ddH₂O; Key resources table) and cultivated an/aerobically for 48 hr. The human experimental protocol was approved by the Cantonal Ethics Commission Bern, Switzerland (ethical approval 2017-00573, NCT03554148). Written informed consent was obtained from all patients and the study has been performed in accordance with the Declaration of Helsinki as well as the CONSORT statement.

Mouse handling

Specific pathogen-free C57Bl/6JRccHsd mice (Key resources table) were purchased at the age of 8 weeks from Inotiv (earlier Envigo, the Netherlands) and were housed in ventilated cages in the Central Animal Facility, University of Bern, Switzerland. All experiments were performed in the morning, mice were supplied with a 12 hr light/dark cycle at 22°C and fed ad libitum with chow and water. To minimize cage effects, we mixed mice over several cages and therefore only used female mice. All animal procedures were carried out in accordance with the Swiss guidelines for the care and use of laboratory animals as well as in accordance with the ARRIVE guidelines and were approved by the Animal Care Committee of the Canton of Bern (Switzerland) under the following number: BE41/2022.

CLP sepsis model

To isolate bacteria from mice with abdominal sepsis, CLP was performed as described elsewhere with some minor modifications (Rittirsch et al., 2009). In brief, mice were anesthetized s.c. injecting (3 µl/g body weight) a mixture of fentanyl (0.05 mg/ml), dormicum (5 mg/ml), and medetor (1 mg/ml) and were then shaved and disinfected with Betadine. Mid-line laparotomy was performed (approximately 1 cm) and the cecum was exposed. The proximal one third of the cecum was ligated with Vicryl 4-0 (Ethicon, cat# V1224H) and perforated with a 23 G needle. The cecum was returned to the abdominal cavity and the laparotomy was sutured continuously in two layers with prolene 6-0 (Ethicon, cat# MPP8697H). At the end, the antidote (naloxone [0.1 mg/ml], revertor [5 mg/ml], temgesic [0.3 mg/ml]) was s.c. injected (9 µl/g body weight). A semiquantitative score sheet was used to predict animal postoperative well-being. Mice were evaluated every 4 hr according to the following criteria: appearance, level of consciousness, activity, response to stimulus, eye shape, respiratory rate, and respiratory quality and analgesia was applied if necessary. After 10 hr, abdominal fluid was collected, spread on LB agar plates, and cultivated an/aerobically for 48 hr.

Whole 16S-rRNA Sanger sequencing

Twenty-five colonies cultivated from abdominal fluid of patients and mice each described above were randomly picked and collected in separate sterile Eppendorf tubes and resuspended in 1 ml of sterile PBS. Each sample was centrifuged for 5 min at 20,000×g and washed once with 1 ml sterile PBS. The pellet was resuspended in 20 µl of sterile PBS and samples were incubated 5 min at 100°C. 1 µl was used for PCR using GoTaq G2 Green Master Mix (Key resources table) and the following primers (Key resources table) at a final concentration of 0.2 µM:

-fD1: 5’-AGA-GTT-TGA-TCC-TGG-CTC-AG-3’
-fD2: 5’-AGA-GTT-TGA-TCA-TGG-CTC-AG-3’
-rP1: 5’-ACG-GTT-ACC-TTG-TTA-CGA-CTT-3’

PCR conditions were as follows: Initial 5 min at 94°C for denaturation, followed by 35 cycles of 1 min denaturation at 94°C, 1 min annealing at 43°C, and 2 min extension at 72°C, with a final extension for 10 min at 72°C. This resulted in a PCR product of optimally ~1400–1500 bp. 20 µl PCR product were run on 2% agarose gel for 90 min, cut out and purified using QIAquick Gel Extraction Kit (Key resources table). The amplicon concentration was measured using nanodrop (Thermo Fisher Scientific) and Sanger sequencing was done by Microsynth.

Quantification of released bacterial ATP

Bacteria were aerobically grown in 20 ml LB medium (5 g Bacto Yeast Extract, 10 g Bacto Tryptone, 5 g NaCl in 1 l ddH₂O; Key resources table) overnight (O/N) (16 hr/37°C/200 rpm) and 0.25 ml of O/N culture were diluted in 100 ml fresh LB medium. Up to 24 hr, 0.25 ml bacteria culture were taken at several time points for growth assessment (OD₆₀₀) and 1 ml was taken for ATP quantification. OD₆₀₀ was measured using a Tecan Spark spectrophotometer. The 1 ml sample for ATP quantification was centrifuged for 5 min at 16,000×g, the supernatant was filtered through a 0.2 µm syringe filter and stored at –80°C. ATP was quantified using a luciferin-luciferase-based assay according to the manufacturer’s protocol (ATP Kit SL, Key resources table) and bioluminescence was measured using a Tecan Spark spectrophotometer. In Figure 3, LB medium was supplemented with 1 mM calcium or 0.5 mM EDTA for the controls.

Absolute quantification of bacteria and assessment of viability

Growth culture was set up as described above and after 4 hr (ATP peak), samples were taken to quantify bacteria and assess viability. Bacteria were diluted in PBS and stained using the Cell Viability Kit with BD Liquid Counting Beads (Key resources table) according to the manufacturer’s protocol. In brief, 100 µl of diluted bacterial growth culture was stained with 1 µl TO dye, 1 µl PI dye, and 10 µl of counting beads were added. The sample was acquired on a CytoFlex S (Beckman Coulter), setting the thresholds for the TO- and the PI-channel to 1000 and analysis was done with FlowJo software (Key resources table). Bacterial biomass was calculated to bacteria/ml culture according to the manufacturer’s protocol.

Transformation of E. coli PS

The Keio collection (Key resources table) E. coli PS was aerobically grown in LB medium O/N (16 hr/37°C/200 rpm). 0.5 ml O/N culture was diluted in 35 ml fresh LB medium and incubated until OD₆₀₀ was 0.35–0.45. Cultures were chilled in ice-water and washed two times with ice-cold 20 ml ultrapure water (Thermo Fisher Scientific, cat# 10977035) (20 min/4°C/3200×g). The supernatant was carefully decanted, and the bacterial pellet was gently resuspended by pipetting (no vortex). After the final wash, the pellet was resuspended in 240 µl ice-cold ultrapure water and kept on ice until EP. 80 µl of ice-cold bacterial cells were mixed with 1 µl plasmid (pBAD28==pEMPTY or pHND10==pAPY, 100–200 ng, Key resources table) in chilled 0.1 cm cuvettes (Bio-Rad, cat# 1652089) and immediately electroporated (voltage = 1.8 kV, capacitance = 25 µF, resistance = 200 Ω). Directly after EP, 1 ml of warm LB medium was added to the cuvette, bacteria were transferred to a tube containing 10 ml pre-warmed LB medium and cultivated for 1 hr at 37°C. Then, bacteria were dispersed on LB agar plates supplemented with ampicillin (100 µg/ml) and incubated at 37°C. The next day, three colonies were picked, streaked on a new ampicillin supplemented LB agar plate, and incubated for 24 hr. The following day, two cryostocks were made from single colonies in LB medium supplemented with 20% glycerol.

Bacteria injection sepsis model

The Keio collection (Key resources table) E. coli PS transformed with either pEMPTY or pAPY was aerobically grown O/N (16 hr/37°C/200 rpm) in 20 ml LB medium supplemented with ampicillin (100 µg/ml). PS+pEMPTY and PS+pAPY were washed with PBS (20 min/22°C/3200×g) and resuspended in 20 ml fresh LB medium supplemented with ampicillin (100 µg/ml). To induce the apyrase, L-arabinose (0.03%, Sigma-Aldrich, cat# A3256-25G) was added. After 3 hr, bacteria were washed, resuspended in PBS supplemented with L-arabinose (0.03%) and 2×10⁹ colony forming units were injected i.a. ATP in bacteria cultures and in the abdominal fluid were assessed using the same assay as described above (ATP Kit SL, Key resources table). Mice were evaluated for postoperative well-being every 4 hr as described above. After 4 and 8 hr and when the score reached specific criteria (for the survival experiment), animals were sacrificed using pentobarbital (150 mg/kg body weight) followed by organ collection.

Collection of abdominal fluid, blood, and organs

After pentobarbital injection, the mice were placed on a surgical tray, fixed, the abdomen was shaved, the abdominal skin was disinfected with Betadine and the skin (but not peritoneum) was cut. Abdominal cells were isolated as described elsewhere with some modifications (Ray and Dittel, 2010). In brief, a 22 G peripheral IV catheter was inserted into the abdominal cavity through the peritoneum. The abdominal cavity was flushed two times with 5 ml MACS buffer (PBS supplemented with 3% FBS [Gibco, cat# 10500-064], 2% HEPES [Sigma-Aldrich, cat# H0887-100ml], and 2 mM EDTA [Sigma-Aldrich, cat# E5134-500G]). The first 5 ml were used to flush the upper abdomen under pressure, and the second 5 ml, to flush the lower abdomen under pressure. Part of the aspirated fluid was used for aerobic plating, if needed, and the rest was centrifuged for 5 min at 700×g to pellet the abdominal cells for various downstream applications. To collect blood, the peritoneum was opened. 300 µl blood was collected from the inferior vena cava using a 22 G peripheral IV catheter and a 1 ml syringe, which was prefilled with 30 µl 2 mM EDTA. Before organ collection (lungs, liver, kidney, and spleen), the mouse was flushed with 5 ml PBS. Organs were excised and used for downstream processing.

Digestion of organs and preparation of single-cell suspension

Harvested organs were digested (Key resources table; kidney and lungs: 1 mg/ml Col I+1 mg/ml Col IV+1 mg/ml Col D+0.1 mg/ml DNase I in DMEM [Gibco, cat# 31966-047]+3% FBS for 30 min; liver: 1 mg/ml Col IV+0.1 mg/ml DNase I in DMEM+3% FBS for 20 min) at 37°C with a spinning magnet or gently pushed through a 100 µm mesh (spleen). After washing with MACS buffer (5 min/4°C/700×g), erythrocytes were lysed using self-made RBC buffer (90 g NH₄Cl, 10 g KHCO₃, 370 mg EDTA in 1 l ddH₂O for 10× stock). Cells were washed again and stained as described below.

Staining of cells and flow cytometry

First, viability dye (Key resources table) and Fc-block (Key resources table) were diluted in PBS and cells were incubated for 20 min at 4°C in the dark. Cells were washed with MACS buffer and surface staining was done with the listed antibody cocktail:

(Key resources table: Ly-6G FITC, Ly-6C PerCP-Cy5.5 or Ly-6C PE-Cy7, CD11b APC, CD206 AF700, CD11c APC-eFluor780, CD45 efluor450 or CD45 APC-Cy7, CD19 Super Bright 600, CD3 BV605, NK1.1 BV605, CCR2 BV650, I-A/I-E BV711, CX3CR1 BV785, Siglec F PE, FcεR1α PE/Dazzle 594, CD115 PE-Cy7, F4/80 BUV395)

for 20 min at 4°C in the dark. Cells were washed again and resuspended in MACS buffer for acquisition on an LSR-Fortessa (BD Biosciences). Analysis was done with FlowJo software (Key resources table) and OMIQ web-based analysis platform (https://www.omiq.ai/). To preserve the global structure of abdominal cell populations, uniform manifold approximation and projection was used as dimensionality reduction technique and cell populations were defined using FlowSOM clustering algorithm (Van Gassen et al., 2015).

Absolute quantification of bacteria by plating

To count bacteria in isolated abdominal fluid, blood, or growth cultures, serial dilutions were done (1 to 1:100,000) and 50 µl of each dilution was streaked on LB agar plates and aerobically incubated. Plates which had between 20 and 200 colony forming units were used for quantification.

Collection of OMV and ATP measurement of OMV

E. coli PS or hypervesiculation mutants from the Keio collection were grown in LB medium for 5 hr, O/N (16 hr) or 24 hr at 37°C and 200 rpm. Bacteria cultures were then centrifuged (20 min/4°C/3200×g) to pellet bacteria. The supernatant was filtered through a 0.45 µm PES filter (Key resources table) and ultracentrifuged (1.5 hr/4°C/150,000×g) to pellet OMV. When ATP within OMV was measured, OMV were washed in PBS and directly stored at –80°C. ATP was quantified using a luciferin-luciferase-based assay according to the manufacturer’s protocol (Microbial ATP Kit HS, Key resources table) and bioluminescence was measured using Tecan Spark spectrophotometer.

If OMV were used for characterization or i.a. injection, first ultracentrifugation was followed by a density gradient ultracentrifugation using OptiPrep (Iodixanol, STEMCELL Technologies, cat# 07820). OMV were resuspended in 50% OptiPrep and OptiPrep gradient (10%, 20%, 30%, 40%, 45%, 50%) was made in underlay technique starting with the 10% layer. Samples were ultracentrifuged (16 hr/4°C/150,000×g) and six fractions (fractions 1, 2, 3a, 3b, 4, and 5) were defined. Fractions were washed separately with PBS (1.5 hr/4°C/150,000×g) and the amount of OMV was determined measuring protein concentration using BCA assay according to the manufacturer’s protocol (Thermo Fisher Scientific, cat# 23227). For experiments, only OMV from fraction 3 were used, which were washed with PBS (1.5 hr/4°C/150,000×g), resuspended in PBS, and stored at –80°C until further processing.

EP and staining of OMV

If EP and staining of OMV was performed, OMV were thawed, pelleted (1.5 hr/4°C/150,000×g), the pellet was resuspended in 720 µl EP buffer (500 mM sucrose and 1 ml glycerol in 10 ml ultrapure water) and kept on ice. This suspension was mixed with either 80 µl EP buffer (control) or 80 µl 10 mM ATP (or ATPγs for RNA sequencing experiment) (Key resources table), filled in chilled 0.4 mm EP cuvettes (Bio-Rad, cat# 1652088) and immediately electroporated (voltage = 1100 V, capacitance = 50 µF, resistance = 100 Ω). After EP, the OMV were 1:1 diluted in warm PBS and kept at 37°C for 20 min. DiI (Key resources table) was added 1:100 to the sample during the incubation time. OMV suspension was then washed with PBS (1.5 hr/4°C/150,000×g).

OMV injection sepsis model

After the final wash in PBS (see above), OMV were resuspended in NaCl 0.9% and filtered through a 0.45 µm centrifuge filter tube (Sigma-Aldrich, cat# CLS8162-96EA). The final OMV suspension was quantified using a BCA assay. 25 µg of either ATP-loaded OMV or empty OMV were i.a. injected and mice were evaluated as described above. After 1 hr, the animal was sacrificed using pentobarbital followed by organ collection. Tissue digestion and flow cytometry was done as described above.

Assessment of ATP release by OMV

OMV were electroporated as described above. After washing in PBS (1.5 hr/4°C/150,000×g), the OMV pellet was resuspended in 6 ml warm PBS and incubated at 37°C. At baseline, after 1, 3, 5, 10, and 24 hr, 1 ml was taken and washed with PBS (1.5 hr/4°C, 150,000×g). The OMV pellet was then resuspended in 200 µl PBS to assess protein concentration using a BCA assay, and ATP in OMV was quantified using a luciferin-luciferase-based assay according to the manufacturer’s protocol (Intracellular ATP Kit HS, Key resources table). Bioluminescence was measured using a Tecan Spark spectrophotometer.

SDS-PAGE, protein staining, and western blot

20 µl of diluted E. coli culture and 20 µl of the different OMV fractions (except fraction 1, since no protein could be detected) were diluted 1:1 with Laemmli/βME (Laemmli buffer solution containing 5% β-mercaptoethanol). The mixture was heated at 100°C for 5 min, shortly centrifuged at 13,000 rpm and loaded on Mini-PROTEAN TGX Gels (Bio-Rad, cat# 4561094). Bio-Rad marker (6 µl) was added to one well and the gel was run at 100 V for 1.5 hr. The gel was then either directly stained with Coomassie blue or transferred to a membrane.

Coomassie blue staining was done as follows: The gel was washed in ddH₂O and the staining solution (Coomassie blue 0.1%, 40% ethanol, 10% acetic acid) was heated for 15 s in the microwave. Warm staining solution was added to the gel and gently shaken for 15 min. Then, staining solution was removed, and the gel was washed with ddH₂O. Destaining solution (10% ethanol, 7.5% acetic acid) was added for 1 hr, exchanged and left O/N.

To transfer the proteins to a membrane, iBlot2 (Invitrogen) was used. Membranes were then blocked with 4% milk/PBS for 1 hr. FtsZ-antibody (1:200, Key resources table) and ompF-antibody (1:500, Key resources table) were added and incubated O/N at 4°C. The next day, membranes were washed with PBS Tween (PBST, 0.05%) three times for 5 min. Secondary fluorescent antibody was then added in milk (1:10,000, Key resources table) and membrane was incubated for 1 hr. The membrane was washed again with PBST three times for 5 min and then scanned using a Licor Odyssey.

Nanoparticle tracking analysis

Size distribution of OMV was analyzed using the NanoSight NS300 Instrument (Malvern Panalytical, 405 nm laser) according to the manufacturer’s protocols. OMV were resuspended in PBS and serial dilutions (1 to 1:100,000) were used to find suitable concentrations. Each experimental sample was analyzed five times. PBS was used to flush the system between the samples and to assess background. For each sample, the relative amount of OMV and the OMV size was recorded, which resulted in a size distribution curve. NTA 2.3 software was used to analyze the data and the following script was used for acquisition (Gheinani et al., 2018): SETTEMP 25; CAMERAON; CAMERAGAIN 12; CAMERALEVEL 11; REPEATSTART; SYRINGLOAD 100; DELAY 10; SYRINGSTOP; DELAY 15; CAPTURE 60; DELAY 1; REPEAT 4; SETTEMP OFF; PROCESSINGLESETTING; EXPORTRESULTS.

Electron microscopy negative staining

For imaging of negatively stained samples, 5 µl of OMV suspension were adsorbed on glow discharged carbon-coated 400 mesh copper grids (Plano) for 1–5 min. After washing the grids three times by dipping in ultrapure water, the grids were stained with 2% uranyl acetate solution (Electron Microscopy Science) in water for 45 s. The excess fluid was removed by gently pushing the grids sideways onto filter paper. The grids were then examined with an FEI Tecnai Spirit transmission electron microscope at 80 kV, which was equipped with a Veleta TEM CCD camera (Olympus).

Immunofluorescent microscopy

One hour after i.a. injection of DiI-stained OMV, lungs were digested as described above. Single-cell suspension was either fixed and imaged or live cells were imaged. For the fixed approach, single-cell suspension was immunolabeled with FITC-tagged anti-Ly-6G (Key resources table) at 1:100 dilution for 20 min at 4°C in the dark to distinguish neutrophils. Cells were washed once with PBS and applied onto glass slides using Cytospin (Thermo Shandon) for 5 min (1800 rpm). Slides were air-dried for 2 min, washed with PBS, and fixed using 4% paraformaldehyde solution for 10 min. Cell nuclei were stained with DAPI (Key resources table) at 1:5000 concentration in IF buffer (0.25% BSA, 0.1% Triton X-100 in PBS) for 1.5 hr at room temperature in the dark. After washing 3×5 min with IF buffer, the slides were covered and sealed with nail polish.

If live cells were imaged, single-cell suspension was concurrently immunolabeled and stained with Hoechst 33342 (Key resources table) at 1:1000 dilution for cell nuclei, FITC-tagged anti-Ly-6G (Key resources table) at 1:100 dilution for neutrophils and LysoTracker Deep Red (Key resources table) at 1:1000 dilution for lysosomes for 30 min at 37°C in the dark. Cells were washed with MACS buffer and immediately imaged.

Fluorescence images were taken using either a Zeiss LSM710 or a Zeiss LSM980 inverted confocal laser scanning microscope equipped with a ×63 (NA1.4) oil immersion objective. Detector wavelength cutoffs were set to minimize signal crosstalk between fluorophores.

RNA isolation from pulmonary neutrophils

One hour after OMV i.a. injection, lungs were digested as described above. One animal had to be excluded, since the surgical time point has been missed. Neutrophils were isolated from single-cell suspension using Streptavidin MicroBeads (Miltenyi Biotec, cat# 130-048-101) according to the manufacturer’s protocol. In brief, cells were counted and incubated with a biotinylated anti-mouse Ly-6G antibody (Key resources table) for 20 min at 4°C. After washing, Streptavidin MicroBeads were added and incubated for 20 min at 4°C. After washing, a MidiMACS separator (Miltenyi Biotec, cat# 130-042-302) together with an LS column (Miltenyi Biotec, cat# 130-042-401) was used to isolate neutrophils and purity of positively selected neutrophils as well as unlabeled cells was assessed by flow cytometry (Key resources table: Ly-6C PE-Cy7, CD11b APC). Neutrophils were pelleted, and supernatant was removed by pipetting. Neutrophils were snap-frozen and stored at –80°C. RNA was isolated directly from frozen neutrophils pellets using Promega ReliaPrep RNA Cell Miniprep System (Key resources table) according to the manufacturer’s protocol and quality was assessed using Bioanalyzer and RNA 6000 Nano Kit (RQN 5.8–9.6, median 7.55). Samples were snap-frozen and stored at –80°C until further processing by the Next Generation Sequencing Platform, University of Bern, https://www.ngs.unibe.ch/.

RNA sequencing

RNA sequencing libraries were prepared using Lexogen CORALL total RNA-seq library kit according to the manufacturer’s protocol, which includes an rRNA depletion step. Sequencing was performed on an Illumina NovaSeq6000 SP flow cell, 2×50 cycles.

Alignment and quantification

The resulting fastq files were quality controlled using fastqc v0.11.9 (Babraham Bioinformatics, 2024). Forward R1 reads were debarcoded by moving the first 12 nucleotides on the 5' end to the name of the read via fastp v0.19.5 (Chen et al., 2018). The alignment was performed with STAR v2.7.10a_alpha_220818 (Dobin et al., 2013). First, a genome index was generated from the mouse reference genome GRCm39 ENSEMBL v108. Second, the reads were then aligned to the reference using STAR with default parameters. Gene read counts were quantified using featureCounts from subread v2.0.1 using the mm108 GTF annotation with default parameters (Liao et al., 2014).

Data visualization

The data from the read count matrix was normalized to reads per million and log-transformed, x → log(1+x). The resulting data was used for principal component analysis, which was performed with the R function prcomp and visualized with a custom script using ggplot2 (Wickham, 2016).

Differential gene expression

Differentially expressed genes were computed using the R package DESeq2 (Love et al., 2014).

Pathway enrichment analysis

The differentially expressed genes obtained from DESeq2 with an adjusted p-value below 0.01 were uploaded to Metascape for pathway analysis on December 5, 2023 (Zhou et al., 2019).

Heatmaps

The lists of genes of the pathways of interest were obtained from genome.jp for the KEGG pathways and using the R function gconvert from the R package gprofiler2 otherwise (Kolberg and Raudvere, 2023). The log-transformed data was used and the heatmaps were done with the heatmap.2 function of the R package gplots with the hierarchical cluster method ‘complete’ using Pearson’s correlation distance (Warnes et al., 2022).

Volcano plot

The volcano plots were performed with the R package ggplot2 and a custom R script (Wickham, 2016).

Statistical analysis

Descriptive statistics and statistical tests were performed using Prism software (Key resources table) or R and RStudio (Key resources table). For differences between two groups a t-test was applied when data was normally distributed (parametric). Otherwise, a Wilcoxon rank-sum test was used (nonparametric). For differences between more than two groups, a one-way ANOVA followed by a Tukey post hoc test (parametric), or a Kruskal-Wallis test followed by a pairwise Wilcoxon rank-sum test with Benjamini-Hochberg correction (nonparametric) was used. For survival analyses, a log-rank test was used. No one-tailed tests were used. No method was used to predetermine experimental sample sizes. A linear model and the correlation between ATP and OD₆₀₀ in Figure 2 and Figure 3 were computed using the R functions lm and cor.test with the following parameters:

stats::cor.test(data$variableATP, data$variablegrowth, alternative = "two.sided", method = "pearson") summary(stats::lm(variableATP~variablegrowth, data = data)).

p<0.05 (P==padj, when correction for multiple testing was necessary) was considered significant in all statistical analyses unless stated otherwise in the figure legend. Significant differences are in italic.

Acknowledgements

We are grateful for the technical and financial support of the Inselspital, the DBMR, and our laboratory. A special thanks goes to Dana Leuenberger and Isabel Büchi for their support with the animal experiments and microscopy. We also want to thank the Microscopy Imaging Center (MIC) of the University of Bern for their assistance in sample preparation and imaging on the electron microscope. We want to thank Prof. Dr. Fabio Grassi and his group for providing us with the pBAD28 and pHND10 plasmids. We also want to thank Prof. Dr. Siegfried Hapfelmeier, Dr. Olivier Schären, and Prof. Dr. Torsten Seuberlich for their extremely helpful scientific support. We want to thank Prof. Dr. Andrew Macpherson for supporting us with his expertise and providing us with the Keio collection. Finally, we want to thank Prof. Dr. Joel Zindel and Dr. Felix Baier for their critical contributions and ideas to complete this project. Figures were created using BioRender.com.

This work was supported by the Swiss National Science Foundation (No.: 166594) to GB.

Appendix 1

Appendix 1—key resources table.

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Strain, strain background (Mus musculus, female)	Wild-type mice	Inotiv, the Netherlands	C57Bl/6JRccHsd
Strain, strain background (Enterococcus faecalis)	Iso1	This paper	NA	See Materials and methods: Human data
Strain, strain background (Escherichia coli)	Iso2	This paper	NA	See Materials and methods: Human data
Strain, strain background (Klebsiella pneumoniae)	Iso3	This paper	NA	See Materials and methods: Human data
Strain, strain background (Staphylococcus aureus)	Iso4	This paper	NA	See Materials and methods: Human data
Strain, strain background (E. faecalis)	Iso5	This paper	NA	See Materials and methods: CLP sepsis model
Strain, strain background (E. coli)	Iso6	This paper	NA	See Materials and methods: CLP sepsis model
Strain, strain background (S. aureus)	Iso7	This paper	NA	See Materials and methods: CLP sepsis model
Strain, strain background (E. coli)	Parental strain (PS)	Keio collection; Baba et al., 2006	BW25113
Strain, strain background (E. coli)	ΔcyoA	Keio collection; Baba et al., 2006	JW0422-1	See Figure 2
Strain, strain background (E. coli)	ΔcyoB	Keio collection; Baba et al., 2006	JW0421-1	See Figure 2
Strain, strain background (E. coli)	ΔcyoC	Keio collection; Baba et al., 2006	JW0420-1	See Figure 2
Strain, strain background (E. coli)	ΔcyoD	Keio collection; Baba et al., 2006	JW0419-1	See Figure 2
Strain, strain background (E. coli)	ΔatpA	Keio collection; Baba et al., 2006	JW3712-1	See Figure 2
Strain, strain background (E. coli)	ΔatpB	Keio collection; Baba et al., 2006	JW3716-1	See Figure 2
Strain, strain background (E. coli)	ΔatpC	Keio collection; Baba et al., 2006	JW3709-2	See Figure 2
Strain, strain background (E. coli)	ΔatpD	Keio collection; Baba et al., 2006	JW3710-1	See Figure 2
Strain, strain background (E. coli)	ΔatpE	Keio collection; Baba et al., 2006	JW3715-1	See Figure 2
Strain, strain background (E. coli)	ΔatpF	Keio collection; Baba et al., 2006	JW3714-2	See Figure 2
Strain, strain background (E. coli)	ΔatpH	Keio collection; Baba et al., 2006	JW3713-1	See Figure 2
Strain, strain background (E. coli)	ΔompF	Keio collection; Baba et al., 2006	JW0912-1	See Figure 3
Strain, strain background (E. coli)	ΔompC	Keio collection; Baba et al., 2006	JW2203-1	See Figure 3
Strain, strain background (E. coli)	ΔlamB	Keio collection; Baba et al., 2006	JW3996-1	See Figure 3
Strain, strain background (E. coli)	ΔphoE	Keio collection; Baba et al., 2006	JW0231-1	See Figure 3
Strain, strain background (E. coli)	ΔmlaA	Keio collection; Baba et al., 2006	JW2343-1	See Figure 5
Strain, strain background (E. coli)	ΔmlaE	Keio collection; Baba et al., 2006	JW3161-1	See Figure 5
Strain, strain background (E. coli)	ΔnlpI	Keio collection; Baba et al., 2006	JW3132-1	See Figure 5
Strain, strain background (E. coli)	ΔtolB	Keio collection; Baba et al., 2006	JW5100-1	See Figure 5
Strain, strain background (E. coli)	ΔdegP	Keio collection; Baba et al., 2006	JW0157-1	See Figure 5
Strain, strain background (E. coli)	ΔrfaD	Keio collection; Baba et al., 2006	JW3594-1	See Figure 5
Strain, strain background (E. coli)	ΔrodZ	Keio collection; Baba et al., 2006	JW2500-1	See Figure 5
Antibody	Purified anti-Ms CD16/32, monoclonal	BioLegend	Cat# 101302; clone 93; Lot# B298973; RRID: AB_312801	(1:200)
Antibody	Rat anti-Ms Ly-6G (FITC), monoclonal	BD Biosciences	Cat# 551460; clone 1A8; Lot# 9068981; RRID: AB_394207	(1:100)
Antibody	Rat anti-Ms Ly-6C (PerCP-Cyanine5.5), monoclonal	Thermo Fisher Scientific	Cat# 45-5932-82; clone HK1.4; Lot# 2309273; RRID: AB_2723343	(1:100)
Antibody	Rat anti-Ms/Hs CD11b (APC), monoclonal	BioLegend	Cat# 101212; clone M1/70; Lot# B312600; RRID: AB_312795	(1:800)
Antibody	Rat anti-Ms CD206 (AF700), monoclonal	BioLegend	Cat# 141733; clone C068C2; Lot# B278058; RRID: AB_2629636	(1:300)
Antibody	Armenian hamster anti-Ms CD11c (APC-eFluor780), monoclonal	Thermo Fisher Scientific	Cat# 47-0114-80; clone N418; Lot# 2133269; RRID: AB_1548652	(1:300)
Antibody	Rat anti-Ms CD45 (efluor450), monoclonal	Thermo Fisher Scientific	Cat# 48-0451-82; clone 30-F11; Lot# 2005853 RRID: AB_1518806	(1:600)
Antibody	Rat anti-Ms CD19 (Super Bright 600), monoclonal	Thermo Fisher Scientific	Cat# 63-0193-82; clone eBio1D3; Lot# 2366423; RRID: AB_2637308	(1:150)
Antibody	Rat anti-Ms CD3 (BV 605), monoclonal	BioLegend	Cat# 100237; clone 17A2; Lot# B389899; RRID: AB_2562039	(1:100)
Antibody	Mouse anti-Ms NK1.1 (BV605), monoclonal	BioLegend	Cat# 108739; clone PK-136; Lot# B389899; RRID: AB_2562273	(1:150)
Antibody	Rat anti-Ms CCR2 (BV650), monoclonal	BioLegend	Cat# 150613; clone SA203G11; Lot# B294599; RRID: AB_2721553	(1:100)
Antibody	Rat anti-Ms I-A/I-E (BV711), monoclonal	BioLegend	Cat# 107643; clone M5/114.15.2; Lot# B299330; RRID: AB_2565976	(1:600)
Antibody	Mouse anti-Ms CX3CR1 (BV785), monoclonal	BioLegend	Cat# 149029; clone SA011F11; Lot# B304744; RRID: AB_2565938	(1:300)
Antibody	Rat anti-Ms Siglec F (PE), monoclonal	Thermo Fisher Scientific	Cat# 12-1702-80; clone 1RNM44N; Lot# 2252684; RRID: AB_2637129	(1:300)
Antibody	Armenian hamster anti-Ms FcεR1α (PE/Dazzle 594), monoclonal	BioLegend	Cat# 134331; clone MAR-1; Lot# B280348; RRID: AB_2687240	(1:300)
Antibody	Rat anti-Ms CD115 (PE-Cy7), monoclonal	BioLegend	Cat# 135523; clone AFS98; Lot# B268547; RRID: AB_2566459	(1:600)
Antibody	Rat anti-Ms F4/80 (BUV395), monoclonal	BD Biosciences	Cat# 565614; clone T45-2342; Lot# 1104580; RRID: AB_2739304	(1:150)
Antibody	Rat anti-Ms CD45 (APC-Cy7), monoclonal	BioLegend	Cat# 103115; clone 30-F11; Lot# NA; RRID: AB_312980	(1:150)
Antibody	Rat anti-Ms Ly-6C (PE-Cy7), monoclonal	BioLegend	Cat# 128017; clone HK1.4; Lot# B331355; RRID: AB_1732093	(1:600)
Antibody	Rat anti-Ms Ly-6G (Biotin), monoclonal	BioLegend	Cat# 127604; clone 1A8; Lot# B314606; RRID: AB_1186108	(1:600)
Antibody	Rabbit anti-E. coli ftsZ, polyclonal	Agrisera	Cat# AS10715; RRID: AB_10754647	(1:200)
Antibody	Rabbit anti-E. coli ompF, polyclonal	Biorbyt	Cat# orb308741; RRID: NA	(1:500)
Antibody	Goat anti-rabbit, polyclonal	LI-COR Biosciences	Cat# 925-68021; RRID: AB_2713919	(1:10,000)
Recombinant DNA reagent	pBAD28==pEMPTY (plasmid)	Proietti et al., 2019; Santapaola et al., 2006; Scribano et al., 2014	Ampicillin resistance
Recombinant DNA reagent	pHND10==pAPY (plasmid)	Proietti et al., 2019; Santapaola et al., 2006; Scribano et al., 2014	Ampicillin resistance
Sequence-based reagent	fD1	Weisburg et al., 1991	PCR primers	5’-AGA-GTT-TGA-TCC-TGG-CTC-AG-3’
Sequence-based reagent	fD2	Weisburg et al., 1991	PCR primers	5’-AGA-GTT-TGA-TCA-TGG-CTC-AG-3’
Sequence-based reagent	rP1	Weisburg et al., 1991	PCR primers	5’-ACG-GTT-ACC-TTG-TTA-CGA-CTT-3’
Commercial assay or kit	QIAquick Gel Extraction Kit	QIAGEN	Cat# 28706
Commercial assay or kit	ATP Kit SL	BioThema	Cat# 144-041
Commercial assay or kit	Cell Viability Kit with BD Liquid Counting Beads	BD Biosciences	Cat# 349480
Commercial assay or kit	Microbial ATP Kit HS	BioThema	Cat# 266-112
Commercial assay or kit	Intracellular ATP Kit HS	BioThema	Cat# 266-111
Commercial assay or kit	ReliaPrep RNA Cell Miniprep System	Promega	Cat# Z6011
Chemical compound, drug	Bacto Yeast Extract	Gibco	Cat# 212750
Chemical compound, drug	Bacto Tryptone	Gibco	Cat# 211699
Chemical compound, drug	Agar	Sigma-Aldrich	Cat# 05039-500G
Chemical compound, drug	GoTaq G2 Green Master Mix	Promega	Cat# M782A
Chemical compound, drug	Collagenase I (Col I)	Sigma-Aldrich	Cat# C0130-100MG
Chemical compound, drug	Collagenase IV (Col IV)	Worthington	Cat# LS004189
Chemical compound, drug	Collagenase D (Col D)	Roche	Cat# 11088858001
Chemical compound, drug	DNAse I	Roche	Cat# 63792800
Chemical compound, drug	Adenosine 5′-triphosphate disodium salt hydrate (ATP)	Sigma-Aldrich	Cat# 2383-1G
Chemical compound, drug	Adenosine-5'-(γ-thio)-triphosphate, Tetralithium salt (ATPγs)	Jena Bioscience	Cat# NU-406-50
Software, algorithm	GraphPad Prism v9.5.1	Prism GraphPad software	https://www.graphpad.com/
Software, algorithm	FlowJo v10.8.1	FlowJo software	https://www.flowjo.com
Software, algorithm	fastqc v0.11.9	Babraham Bioinformatics, 2024	http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
Software, algorithm	fastp v0.19.5	Chen et al., 2018	https://github.com/OpenGene/fastp RRID:SCR_016962
Software, algorithm	STAR v2.7.10a_alpha_220818	Dobin et al., 2013	https://github.com/alexdobin/STAR RRID:SCR_004463
Software, algorithm	subread v2.0.1	Liao et al., 2014	https://github.com/ShiLab-Bioinformatics/subread RRID:SCR_009803
Software, algorithm	R v4.2.2	The R Project for Statistical Computing	https://cran.r-project.org
Software, algorithm	RStudio v2022.07.2	RStudio Desktop	https://www.rstudio.com
Software, algorithm	R package ggplot2 v3.4.3	Wickham, 2016	https://ggplot2.tidyverse.org
Software, algorithm	R package readxl v1.4.3	Wickham and Bryan, 2023a	https://CRAN.R-project.org/package=readxl
Software, algorithm	R package ggbreak v0.1.2	Xu et al., 2021	https://github.com/YuLab-SMU/ggbreak RRID:SCR_014601
Software, algorithm	R package rstatix v0.7.2	Kassambara, 2023	https://CRAN.R-project.org/package=rstatix
Software, algorithm	R package dplyr v1.0.10	Wickham et al., 2023b	https://CRAN.R-project.org/package=dplyr
Software, algorithm	R package DESeq2 v1.38.3	Love et al., 2014	https://github.com/mikelove/DESeq2 RRID:SCR_015687
Software, algorithm	R package ggrepel v0.9.3	Slowikowski et al., 2023	https://CRAN.R-project.org/package=ggrepel
Software, algorithm	R package vegan v2.6–4	Oksanen et al., 2022	https://github.com/vegandevs/vegan RRID:SCR_011950
Software, algorithm	R package pairwiseAdonis v0.4	Arbizu, 2023	https://github.com/pmartinezarbizu/pairwiseAdonis RRID:SCR_001905
Software, algorithm	R package gprofiler2 v0.2.2	Kolberg and Raudvere, 2023	https://cran.r-project.org/web/packages/gprofiler2/index.html
Software, algorithm	R package gplots v3.1.3	Warnes et al., 2022	https://CRAN.R-project.org/package=gplots
Software, algorithm	R package viridis v0.6.3	Ross et al., 2021	https://sjmgarnier.github.io/viridis/ RRID:SCR_016696
Other	Fixable Viability Dye eFluor506	Thermo Fisher Scientific	Cat# 65-0866-18	(1:600)
Other	Nalgene Rapid-Flow PES Filter Units	Thermo Scientific	Cat# 168-0045, 165-0045, 124-0045PK
Other	Vybrant DiI Cell-Labeling Solution	Invitrogen	Cat# V22885	(1:100)
Other	DAPI	Sigma-Aldrich	Cat# D9542-5MG	(1:5000)
Other	Hoechst 33342	Thermo Fisher Scientific	Cat# H3570	(1:1000)
Other	LysoTracker	Invitrogen	Cat# L12492	(1:1000)

Open in a new tab

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Guido Beldi, Email: guido.beldi@insel.ch.

Kiyoshi Takeda, Osaka University, Japan.

Wendy S Garrett, Harvard T.H. Chan School of Public Health, United States.

Funding Information

This paper was supported by the following grant:

Swiss National Science Foundation 166594 to Guido Beldi.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing.

Formal analysis, Investigation, Writing - original draft.

Data curation, Software, Formal analysis, Visualization.

Investigation.

Data curation, Software, Writing - original draft.

Formal analysis, Investigation.

Investigation, Methodology, Writing - original draft.

Resources, Funding acquisition, Methodology, Writing - original draft, Writing - review and editing.

Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing - original draft, Project administration, Writing - review and editing.

Ethics

NCT03554148.

The human experimental protocol was approved by the Cantonal Ethics Commission Bern, Switzerland (ethical approval 2017-00573, NCT03554148). Written informed consent was obtained from all patients and the study has been performed in accordance with the Declaration of Helsinki as well as the CONSORT statement.

All animal procedures were carried out in accordance with the Swiss guidelines for the care and use of laboratory animals as well as in accordance with the ARRIVE guidelines and were approved by the Animal Care Committee of the Canton of Bern (Switzerland) under the following number: BE41/2022.

Additional files

MDAR checklist

elife-96678-mdarchecklist1.pdf^{(228.1KB, pdf)}

Data availability

RNA sequencing data has been deposited in Gene Expression Omnibus (GEO) under the accession code GSE272296. In addition, all raw data, metadata and code are publicly available at BORIS Portal of the University of Bern under a CC-BY licence: https://doi.org/10.48620/418.

The following datasets were generated:

Spari D, Schmid A, Sánchez-Taltavull D, Murugan S, Keller K, Ennaciri N, Salm L, Stroka D, Beldi G. 2024. Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis. NCBI Gene Expression Omnibus. GSE272296

Beldi G, Keller KA, Sánchez Taltavull D, Murugan S, Schmid AB, Spari D, Ennaciri NS, Salm L, Keogh-Stroka DM. 2024. Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis. BORIS Portal.

References

Alvarez CL, Corradi G, Lauri N, Marginedas-Freixa I, Leal Denis MF, Enrique N, Mate SM, Milesi V, Ostuni MA, Herlax V, Schwarzbaum PJ. Dynamic regulation of extracellular ATP in Escherichia coli. The Biochemical Journal. 2017;474:1395–1416. doi: 10.1042/BCJ20160879. [DOI] [PubMed] [Google Scholar]
Araujo MEG, Liebscher G, Hess MW, Huber LA. Lysosomal size matters. Traffic. 2020;21:60–75. doi: 10.1111/tra.12714. [DOI] [PMC free article] [PubMed] [Google Scholar]
Arbizu PM. pairwiseAdonis. cb190f7GitHub. 2023 https://github.com/pmartinezarbizu/pairwiseAdonis
Atarashi K, Nishimura J, Shima T, Umesaki Y, Yamamoto M, Onoue M, Yagita H, Ishii N, Evans R, Honda K, Takeda K. ATP drives lamina propria T(H)17 cell differentiation. Nature. 2008;455:808–812. doi: 10.1038/nature07240. [DOI] [PubMed] [Google Scholar]
Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Molecular Systems Biology. 2006;2:2006.0008. doi: 10.1038/msb4100050. [DOI] [PMC free article] [PubMed] [Google Scholar]
Babraham Bioinformatics FastQC A quality control tool for high throughput sequence data. Bioinformatics. 2024 http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
Baeza N, Mercade E. Relationship between membrane vesicles, extracellular ATP and biofilm formation in antarctic gram-negative bacteria. Microbial Ecology. 2021;81:645–656. doi: 10.1007/s00248-020-01614-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bielaszewska M, Rüter C, Bauwens A, Greune L, Jarosch KA, Steil D, Zhang W, He X, Lloubes R, Fruth A, Kim KS, Schmidt MA, Dobrindt U, Mellmann A, Karch H. Host cell interactions of outer membrane vesicle-associated virulence factors of enterohemorrhagic Escherichia coli O157: Intracellular delivery, trafficking and mechanisms of cell injury. PLOS Pathogens. 2017;13:e1006159. doi: 10.1371/journal.ppat.1006159. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bittel M, Reichert P, Sarfati I, Dressel A, Leikam S, Uderhardt S, Stolzer I, Phu TA, Ng M, Vu NK, Tenzer S, Distler U, Wirtz S, Rothhammer V, Neurath MF, Raffai RL, Günther C, Momma S. Visualizing transfer of microbial biomolecules by outer membrane vesicles in microbe-host-communication in vivo. Journal of Extracellular Vesicles. 2021;10:e12159. doi: 10.1002/jev2.12159. [DOI] [PMC free article] [PubMed] [Google Scholar]
Bitto NJ, Chapman R, Pidot S, Costin A, Lo C, Choi J, D’Cruze T, Reynolds EC, Dashper SG, Turnbull L, Whitchurch CB, Stinear TP, Stacey KJ, Ferrero RL. Bacterial membrane vesicles transport their DNA cargo into host cells. Scientific Reports. 2017;7:7072. doi: 10.1038/s41598-017-07288-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
Borisov VB, Gennis RB, Hemp J, Verkhovsky MI. The cytochrome bd respiratory oxygen reductases. Biochimica et Biophysica Acta. 2011;1807:1398–1413. doi: 10.1016/j.bbabio.2011.06.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
Burnstock G. In: Purinergic Signaling. Pelegrín P, editor. Springer; 2020. Introduction to purinergic signaling; pp. 1–15. [DOI] [PubMed] [Google Scholar]
Cao M, Wang G, Xie J. Immune dysregulation in sepsis: experiences, lessons and perspectives. Cell Death Discovery. 2023;9:465. doi: 10.1038/s41420-023-01766-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–i890. doi: 10.1093/bioinformatics/bty560. [DOI] [PMC free article] [PubMed] [Google Scholar]
Choi U, Lee CR. Distinct roles of outer membrane porins in antibiotic resistance and membrane integrity in Escherichia coli. Frontiers in Microbiology. 2019;10:953. doi: 10.3389/fmicb.2019.00953. [DOI] [PMC free article] [PubMed] [Google Scholar]
Diekema DJ, Hsueh PR, Mendes RE, Pfaller MA, Rolston KV, Sader HS, Jones RN. The microbiology of bloodstream infection: 20-year trends from the SENTRY antimicrobial surveillance program. Antimicrobial Agents and Chemotherapy. 2019;63:e00355-19. doi: 10.1128/AAC.00355-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ding Q, Quah SY, Tan KS. Secreted adenosine triphosphate from Aggregatibacter actinomycetemcomitans triggers chemokine response. Molecular Oral Microbiology. 2016a;31:423–434. doi: 10.1111/omi.12143. [DOI] [PubMed] [Google Scholar]
Ding Q, Tan KS. The danger signal extracellular ATP is an inducer of Fusobacterium nucleatum biofilm dispersal. Frontiers in Cellular and Infection Microbiology. 2016b;6:155. doi: 10.3389/fcimb.2016.00155. [DOI] [PMC free article] [PubMed] [Google Scholar]
Di Virgilio F, Sarti AC, Coutinho-Silva R. Purinergic signaling, DAMPs, and inflammation. American Journal of Physiology. Cell Physiology. 2020;318:C832–C835. doi: 10.1152/ajpcell.00053.2020. [DOI] [PubMed] [Google Scholar]
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21. doi: 10.1093/bioinformatics/bts635. [DOI] [PMC free article] [PubMed] [Google Scholar]
Dosch M, Zindel J, Jebbawi F, Melin N, Sanchez-Taltavull D, Stroka D, Candinas D, Beldi G. Connexin-43-dependent ATP release mediates macrophage activation during sepsis. eLife. 2019;8:e42670. doi: 10.7554/eLife.42670. [DOI] [PMC free article] [PubMed] [Google Scholar]
Eichelberger KR, Goldman WE. Manipulating neutrophil degranulation as a bacterial virulence strategy. PLOS Pathogens. 2020;16:e1009054. doi: 10.1371/journal.ppat.1009054. [DOI] [PMC free article] [PubMed] [Google Scholar]
Eltzschig HK, Sitkovsky MV, Robson SC. Purinergic signaling during inflammation. The New England Journal of Medicine. 2012;367:2322–2333. doi: 10.1056/NEJMra1205750. [DOI] [PMC free article] [PubMed] [Google Scholar]
Fu S, Wang Y, Xia X, Zheng JC. Exosome engineering: Current progress in cargo loading and targeted delivery. NanoImpact. 2020;20:100261. doi: 10.1016/j.impact.2020.100261. [DOI] [Google Scholar]
Galber C, Carissimi S, Baracca A, Giorgio V. The ATP synthase deficiency in human diseases. Life. 2021;11:325. doi: 10.3390/life11040325. [DOI] [PMC free article] [PubMed] [Google Scholar]
Gheinani AH, Vögeli M, Baumgartner U, Vassella E, Draeger A, Burkhard FC, Monastyrskaya K. Improved isolation strategies to increase the yield and purity of human urinary exosomes for biomarker discovery. Scientific Reports. 2018;8:3945. doi: 10.1038/s41598-018-22142-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ghosn EEB, Cassado AA, Govoni GR, Fukuhara T, Yang Y, Monack DM, Bortoluci KR, Almeida SR, Herzenberg LA, Herzenberg LA. Two physically, functionally, and developmentally distinct peritoneal macrophage subsets. PNAS. 2010;107:2568–2573. doi: 10.1073/pnas.0915000107. [DOI] [PMC free article] [PubMed] [Google Scholar]
Grauel A, Kägi J, Rasmussen T, Makarchuk I, Oppermann S, Moumbock AFA, Wohlwend D, Müller R, Melin F, Günther S, Hellwig P, Böttcher B, Friedrich T. Structure of Escherichia coli cytochrome bd-II type oxidase with bound aurachin D. Nature Communications. 2021;12:6498. doi: 10.1038/s41467-021-26835-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Hironaka I, Iwase T, Sugimoto S, Okuda K, Tajima A, Yanaga K, Mizunoe Y. Glucose triggers ATP secretion from bacteria in a growth-phase-dependent manner. Applied and Environmental Microbiology. 2013;79:2328–2335. doi: 10.1128/AEM.03871-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ihssen J, Jovanovic N, Sirec T, Spitz U. Real-time monitoring of extracellular ATP in bacterial cultures using thermostable luciferase. PLOS ONE. 2021;16:e0244200. doi: 10.1371/journal.pone.0244200. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ivancic V, Mastali M, Percy N, Gornbein J, Babbitt JT, Li Y, Landaw EM, Bruckner DA, Churchill BM, Haake DA. Rapid antimicrobial susceptibility determination of uropathogens in clinical urine specimens by use of ATP bioluminescence. Journal of Clinical Microbiology. 2008;46:1213–1219. doi: 10.1128/JCM.02036-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
Iwase T, Shinji H, Tajima A, Sato F, Tamura T, Iwamoto T, Yoneda M, Mizunoe Y. Isolation and identification of ATP-secreting bacteria from mice and humans. Journal of Clinical Microbiology. 2010;48:1949–1951. doi: 10.1128/JCM.01941-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
Jang SC, Kim SR, Yoon YJ, Park KS, Kim JH, Lee J, Kim OY, Choi EJ, Kim DK, Choi DS, Kim YK, Park J, Di Vizio D, Gho YS. In vivo kinetic biodistribution of nano-sized outer membrane vesicles derived from bacteria. Small. 2015;11:456–461. doi: 10.1002/smll.201401803. [DOI] [PubMed] [Google Scholar]
Junger WG. Immune cell regulation by autocrine purinergic signalling. Nature Reviews. Immunology. 2011;11:201–212. doi: 10.1038/nri2938. [DOI] [PMC free article] [PubMed] [Google Scholar]
Juodeikis R, Carding SR. Outer membrane vesicles: Biogenesis, functions, and issues. Microbiology and Molecular Biology Reviews. 2022;86:e0003222. doi: 10.1128/mmbr.00032-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kassambara A. Rstatix: pipe-friendly framework for basic statistical tests. 0.7.2R Packages. 2023 https://cran.r-project.org/web/packages/rstatix/index.html
Kim JH, Yoon YJ, Lee J, Choi EJ, Yi N, Park KS, Park J, Lötvall J, Kim YK, Gho YS. Outer membrane vesicles derived from Escherichia coli up-regulate expression of endothelial cell adhesion molecules in vitro and in vivo. PLOS ONE. 2013;8:e59276. doi: 10.1371/journal.pone.0059276. [DOI] [PMC free article] [PubMed] [Google Scholar]
Koch AL. Death of bacteria in growing culture. Journal of Bacteriology. 1959;77:623–629. doi: 10.1128/jb.77.5.623-629.1959. [DOI] [PMC free article] [PubMed] [Google Scholar]
Kolberg L, Raudvere U. Gprofiler2: interface to the “g:profiler” toolset. 0.2.2R Packages. 2023 https://cran.r-project.org/web/packages/gprofiler2/index.html
Kulp A, Kuehn MJ. Biological functions and biogenesis of secreted bacterial outer membrane vesicles. Annual Review of Microbiology. 2010;64:163–184. doi: 10.1146/annurev.micro.091208.073413. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ledderose C, Bao Y, Kondo Y, Fakhari M, Slubowski C, Zhang J, Junger WG. Purinergic signaling and the immune response in sepsis: A review. Clinical Therapeutics. 2016;38:1054–1065. doi: 10.1016/j.clinthera.2016.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Leduc M, van Heijenoort J. Autolysis of Escherichia coli. Journal of Bacteriology. 1980;142:52–59. doi: 10.1128/jb.142.1.52-59.1980. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lee EY, Bang JY, Park GW, Choi DS, Kang JS, Kim HJ, Park KS, Lee JO, Kim YK, Kwon KH, Kim KP, Gho YS. Global proteomic profiling of native outer membrane vesicles derived from Escherichia coli. PROTEOMICS. 2007;7:3143–3153. doi: 10.1002/pmic.200700196. [DOI] [PubMed] [Google Scholar]
Lee J, Yoon YJ, Kim JH, Dinh NTH, Go G, Tae S, Park KS, Park HT, Lee C, Roh TY, Di Vizio D, Gho YS. Outer membrane vesicles derived from Escherichia coli regulate neutrophil migration by induction of endothelial IL-8. Frontiers in Microbiology. 2018;9:2268. doi: 10.3389/fmicb.2018.02268. [DOI] [PMC free article] [PubMed] [Google Scholar]
Leive L. Studies on the permeability change produced in coliform bacteria by ethylenediaminetetraacetate. The Journal of Biological Chemistry. 1968;243:2373–2380. [PubMed] [Google Scholar]
Lennaárd AJ, Mamand DR, Wiklander RJ, El Andaloussi S, Wiklander OPB. Optimised electroporation for loading of extracellular vesicles with doxorubicin. Pharmaceutics. 2021;14:38. doi: 10.3390/pharmaceutics14010038. [DOI] [PMC free article] [PubMed] [Google Scholar]
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–930. doi: 10.1093/bioinformatics/btt656. [DOI] [PubMed] [Google Scholar]
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014;15:550. doi: 10.1186/s13059-014-0550-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
Lundin A. In: Methods in Enzymology. Lundin A, editor. Elsevier; 2000. Use of firefly luciferase in atp-related assays of biomass, enzymes, and metabolites; pp. 346–370. [DOI] [PubMed] [Google Scholar]
McBroom AJ, Johnson AP, Vemulapalli S, Kuehn MJ. Outer membrane vesicle production by Escherichia coli is independent of membrane instability. Journal of Bacteriology. 2006;188:5385–5392. doi: 10.1128/JB.00498-06. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mempin R, Tran H, Chen C, Gong H, Kim Ho K, Lu S. Release of extracellular ATP by bacteria during growth. BMC Microbiology. 2013;13:301. doi: 10.1186/1471-2180-13-301. [DOI] [PMC free article] [PubMed] [Google Scholar]
Michel LV, Gaborski T. Outer membrane vesicles as molecular biomarkers for Gram-negative sepsis: Taking advantage of nature’s perfect packages. The Journal of Biological Chemistry. 2022;298:102483. doi: 10.1016/j.jbc.2022.102483. [DOI] [PMC free article] [PubMed] [Google Scholar]
Mureșan MG, Balmoș IA, Badea I, Santini A. Abdominal sepsis: An update. The Journal of Critical Care Medicine. 2018;4:120–125. doi: 10.2478/jccm-2018-0023. [DOI] [PMC free article] [PubMed] [Google Scholar]
Oksanen J, Simpson GL, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Solymos P, Stevens MHH, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, Caceres MD, Durand S, Weedon J. Vegan: community ecology package. 2.6-4R Packages. 2022 https://cran.r-project.org/web/packages/vegan/index.html
Orench-Rivera N, Kuehn MJ. Environmentally controlled bacterial vesicle-mediated export. Cellular Microbiology. 2016;18:1525–1536. doi: 10.1111/cmi.12676. [DOI] [PMC free article] [PubMed] [Google Scholar]
Park KS, Choi KH, Kim YS, Hong BS, Kim OY, Kim JH, Yoon CM, Koh GY, Kim YK, Gho YS. Outer membrane vesicles derived from Escherichia coli induce systemic inflammatory response syndrome. PLOS ONE. 2010;5:e11334. doi: 10.1371/journal.pone.0011334. [DOI] [PMC free article] [PubMed] [Google Scholar]
Park KS, Lee J, Jang SC, Kim SR, Jang MH, Lötvall J, Kim YK, Gho YS. Pulmonary inflammation induced by bacteria-free outer membrane vesicles from Pseudomonas aeruginosa. American Journal of Respiratory Cell and Molecular Biology. 2013;49:637–645. doi: 10.1165/rcmb.2012-0370OC. [DOI] [PubMed] [Google Scholar]
Pérez-Cruz C, Carrión O, Delgado L, Martinez G, López-Iglesias C, Mercade E. New type of outer membrane vesicle produced by the Gram-negative bacterium Shewanella vesiculosa M7T: implications for DNA content. Applied and Environmental Microbiology. 2013;79:1874–1881. doi: 10.1128/AEM.03657-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
Pérez-Cruz C, Delgado L, López-Iglesias C, Mercade E. Outer-inner membrane vesicles naturally secreted by gram-negative pathogenic bacteria. PLOS ONE. 2015;10:e0116896. doi: 10.1371/journal.pone.0116896. [DOI] [PMC free article] [PubMed] [Google Scholar]
Perruzza L, Gargari G, Proietti M, Fosso B, D’Erchia AM, Faliti CE, Rezzonico-Jost T, Scribano D, Mauri L, Colombo D, Pellegrini G, Moregola A, Mooser C, Pesole G, Nicoletti M, Norata GD, Geuking MB, McCoy KD, Guglielmetti S, Grassi F. T follicular helper cells promote a beneficial gut ecosystem for host metabolic homeostasis by sensing microbiota-derived extracellular ATP. Cell Reports. 2017;18:2566–2575. doi: 10.1016/j.celrep.2017.02.061. [DOI] [PMC free article] [PubMed] [Google Scholar]
Proietti M, Perruzza L, Scribano D, Pellegrini G, D’Antuono R, Strati F, Raffaelli M, Gonzalez SF, Thelen M, Hardt WD, Slack E, Nicoletti M, Grassi F. ATP released by intestinal bacteria limits the generation of protective IgA against enteropathogens. Nature Communications. 2019;10:250. doi: 10.1038/s41467-018-08156-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
Qureshi OS, Paramasivam A, Yu JCH, Murrell-Lagnado RD. Regulation of P2X4 receptors by lysosomal targeting, glycan protection and exocytosis. Journal of Cell Science. 2007;120:3838–3849. doi: 10.1242/jcs.010348. [DOI] [PubMed] [Google Scholar]
Ray A, Dittel BN. Isolation of mouse peritoneal cavity cells. Journal of Visualized Experiments. 2010;35:1488. doi: 10.3791/1488. [DOI] [PMC free article] [PubMed] [Google Scholar]
Reimer SL, Beniac DR, Hiebert SL, Booth TF, Chong PM, Westmacott GR, Zhanel GG, Bay DC. Comparative analysis of outer membrane vesicle isolation methods with an Escherichia coli tolA mutant reveals a hypervesiculating phenotype with outer-inner membrane vesicle content. Frontiers in Microbiology. 2021;12:628801. doi: 10.3389/fmicb.2021.628801. [DOI] [PMC free article] [PubMed] [Google Scholar]
Reinhart K, Daniels R, Kissoon N, Machado FR, Schachter RD, Finfer S. Recognizing sepsis as a global health priority - A WHO resolution. The New England Journal of Medicine. 2017;377:414–417. doi: 10.1056/NEJMp1707170. [DOI] [PubMed] [Google Scholar]
Rittirsch D, Huber-Lang MS, Flierl MA, Ward PA. Immunodesign of experimental sepsis by cecal ligation and puncture. Nature Protocols. 2009;4:31–36. doi: 10.1038/nprot.2008.214. [DOI] [PMC free article] [PubMed] [Google Scholar]
Robinson LE, Murrell-Lagnado RD. The trafficking and targeting of P2X receptors. Frontiers in Cellular Neuroscience. 2013;7:233. doi: 10.3389/fncel.2013.00233. [DOI] [PMC free article] [PubMed] [Google Scholar]
Ross N, Rudis B, Filipovic-Pierucci A, Galili T, Greenwell C. sjmgarnier/viridis: viridis 0.6.0 (pre-CRAN release) v0.6.0preZenodo. 2021 doi: 10.5281/zenodo.4679424. [DOI]
Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, Colombara DV, Ikuta KS, Kissoon N, Finfer S, Fleischmann-Struzek C, Machado FR, Reinhart KK, Rowan K, Seymour CW, Watson RS, West TE, Marinho F, Hay SI, Lozano R, Lopez AD, Angus DC, Murray CJL, Naghavi M. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. The Lancet. 2020;395:200–211. doi: 10.1016/S0140-6736(19)32989-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Salm L, Shim R, Noskovicova N, Kubes P. Gata6+ large peritoneal macrophages: an evolutionarily conserved sentinel and effector system for infection and injury. Trends in Immunology. 2023;44:129–145. doi: 10.1016/j.it.2022.12.002. [DOI] [PubMed] [Google Scholar]
Santapaola D, Del Chierico F, Petrucca A, Uzzau S, Casalino M, Colonna B, Sessa R, Berlutti F, Nicoletti M. Apyrase, the product of the virulence plasmid-encoded phoN2 (apy) gene of Shigella flexneri, is necessary for proper unipolar IcsA localization and for efficient intercellular spread. Journal of Bacteriology. 2006;188:1620–1627. doi: 10.1128/JB.188.4.1620-1627.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
Schwechheimer C, Kuehn MJ. Outer-membrane vesicles from Gram-negative bacteria: biogenesis and functions. Nature Reviews. Microbiology. 2015;13:605–619. doi: 10.1038/nrmicro3525. [DOI] [PMC free article] [PubMed] [Google Scholar]
Scribano D, Petrucca A, Pompili M, Ambrosi C, Bruni E, Zagaglia C, Prosseda G, Nencioni L, Casalino M, Polticelli F, Nicoletti M. Polar localization of PhoN2, a periplasmic virulence-associated factor of Shigella flexneri, is required for proper IcsA exposition at the old bacterial pole. PLOS ONE. 2014;9:e90230. doi: 10.1371/journal.pone.0090230. [DOI] [PMC free article] [PubMed] [Google Scholar]
Slowikowski K, Schep A, Hughes S, Dang TK, Lukauskas S, Irisson JO, Kamvar ZN, Ryan T, Christophe D, Hiroaki Y, Gramme P, Abdol AM, Barrett M, Cannoodt R, Krassowski M, Chirico M, Aphalo P, Barton F. Ggrepel: automatically position non-overlapping text labels with “ggplot2.”. 0.9.5R Packages. 2023 https://cran.r-project.org/web/packages/ggrepel/index.html
Spari D, Beldi G. Extracellular ATP as an inter-kingdom signaling molecule: Release Mechanisms by bacteria and its implication on the host. International Journal of Molecular Sciences. 2020;21:5590. doi: 10.3390/ijms21155590. [DOI] [PMC free article] [PubMed] [Google Scholar]
Takaki K, Tahara YO, Nakamichi N, Hasegawa Y, Shintani M, Ohkuma M, Miyata M, Futamata H, Tashiro Y. Multilamellar and multivesicular outer membrane vesicles produced by a buttiauxella agrestis tolB Mutant. Applied and Environmental Microbiology. 2020;86:e01131-20. doi: 10.1128/AEM.01131-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
Toyofuku M, Nomura N, Eberl L. Types and origins of bacterial membrane vesicles. Nature Reviews. Microbiology. 2019;17:13–24. doi: 10.1038/s41579-018-0112-2. [DOI] [PubMed] [Google Scholar]
Tsubaki M, Hori H, Mogi T. Probing molecular structure of dioxygen reduction site of bacterial quinol oxidases through ligand binding to the redox metal centers. Journal of Inorganic Biochemistry. 2000;82:19–25. doi: 10.1016/s0162-0134(00)00140-9. [DOI] [PubMed] [Google Scholar]
Turnbull L, Toyofuku M, Hynen AL, Kurosawa M, Pessi G, Petty NK, Osvath SR, Cárcamo-Oyarce G, Gloag ES, Shimoni R, Omasits U, Ito S, Yap X, Monahan LG, Cavaliere R, Ahrens CH, Charles IG, Nomura N, Eberl L, Whitchurch CB. Explosive cell lysis as a mechanism for the biogenesis of bacterial membrane vesicles and biofilms. Nature Communications. 2016;7:11220. doi: 10.1038/ncomms11220. [DOI] [PMC free article] [PubMed] [Google Scholar]
Turner L, Praszkier J, Hutton ML, Steer D, Ramm G, Kaparakis-Liaskos M, Ferrero RL. Increased outer membrane vesicle formation in a Helicobacter pylori tolB mutant. Helicobacter. 2015;20:269–283. doi: 10.1111/hel.12196. [DOI] [PubMed] [Google Scholar]
Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, Saeys Y. FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data. Cytometry. Part A. 2015;87:636–645. doi: 10.1002/cyto.a.22625. [DOI] [PubMed] [Google Scholar]
Vega-Pérez A, Villarrubia LH, Godio C, Gutiérrez-González A, Feo-Lucas L, Ferriz M, Martínez-Puente N, Alcaín J, Mora A, Sabio G, López-Bravo M, Ardavín C. Resident macrophage-dependent immune cell scaffolds drive anti-bacterial defense in the peritoneal cavity. Immunity. 2021;54:2578–2594. doi: 10.1016/j.immuni.2021.10.007. [DOI] [PubMed] [Google Scholar]
Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W, Liaw A, Lumley T, Maechler M, Magnusson A, Moeller S, Schwartz M, Venables B, Galili T. Gplots: various R programming tools for plotting data. 3.1.3R Packages. 2022 https://cran.r-project.org/web/packages/gplots/index.html
Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 16S ribosomal DNA amplification for phylogenetic study. Journal of Bacteriology. 1991;173:697–703. doi: 10.1128/jb.173.2.697-703.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
Wickham H. Ggplot2. Springer International Publishing; 2016. [DOI] [Google Scholar]
Wickham H, Bryan J. readxl: Read Excel Files. 1.4.3R Packages. 2023a https://cran.r-project.org/web/packages/readxl/index.html
Wickham H, François R, Henry L, Müller K. Dplyr: A grammar of data manipulation. 1.1.4R Packages. 2023b https://cran.r-project.org/web/packages/dplyr/index.html
Xu S, Chen M, Feng T, Zhan L, Zhou L, Yu G. Use ggbreak to effectively utilize plotting space to deal with large datasets and outliers. Frontiers in Genetics. 2021;12:774846. doi: 10.3389/fgene.2021.774846. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yamamoto N, Nakahigashi K, Nakamichi T, Yoshino M, Takai Y, Touda Y, Furubayashi A, Kinjyo S, Dose H, Hasegawa M, Datsenko KA, Nakayashiki T, Tomita M, Wanner BL, Mori H. Update on the Keio collection of Escherichia coli single-gene deletion mutants. Molecular Systems Biology. 2009;5:335. doi: 10.1038/msb.2009.92. [DOI] [PMC free article] [PubMed] [Google Scholar]
Yegutkin GG, Mikhailov A, Samburski SS, Jalkanen S. The detection of micromolar pericellular ATP pool on lymphocyte surface by using lymphoid ecto-adenylate kinase as intrinsic ATP sensor. Molecular Biology of the Cell. 2006;17:3378–3385. doi: 10.1091/mbc.e05-10-0993. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nature Communications. 2019;10:1523. doi: 10.1038/s41467-019-09234-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zindel J, Peiseler M, Hossain M, Deppermann C, Lee WY, Haenni B, Zuber B, Deniset JF, Surewaard BGJ, Candinas D, Kubes P. Primordial GATA6 macrophages function as extravascular platelets in sterile injury. Science. 2021;371:eabe0595. doi: 10.1126/science.abe0595. [DOI] [PubMed] [Google Scholar]

eLife. doi: 10.7554/eLife.96678.3.sa0

eLife assessment

Kiyoshi Takeda ¹

This fundamental study advances our understanding of the role of bacterial-derived extracellular ATP in the pathogenesis of sepsis. The evidence supporting the conclusions is compelling, although not all concerns from a previous round of reviews were adequately addressed. The work will be of broad interest to researchers on microbiology and infectious diseases.

eLife. doi: 10.7554/eLife.96678.3.sa1

Reviewer #1 (Public review):

Anonymous

Summary:

Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated to the reduction of small peritoneal macrophages and CX3CR1+ monocytes, and increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting this mechanism could contribute to sepsis severity.

Strengths:

The most compelling part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be pathogenically relevant during systemic dissemination of bacteria in the host.

Weaknesses:

As pointed out in the limitations of the study whether ATP-loaded OMVs could provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differently induced also by apyrase-expressing vs control E. coli transformants. Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcome than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs. Is neutrophils count affected by ATP delivered via OMVs? Probably a comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP.

The analyses performed on OMV treated versus E. coli infected mice are not immediately related and difficult to combine when trying to draw a pathogenetic hypothesis for bacterial ATP in sepsis.

It's not clear why lung neutrophils were used for RNAseq.

eLife. doi: 10.7554/eLife.96678.3.sa2

Reviewer #2 (Public review):

Anonymous

Summary:

In their manuscript, Daniel Spari et al. explored the dual role of ATP in exacerbating sepsis, revealing that ATP from both host and bacteria significantly impacts immune responses and disease progression.

Strengths:

The study meticulously examines the complex relationship between ATP release and bacterial growth, membrane integrity, and how bacterial ATP potentially dampens inflammatory responses, thereby impairing survival in sepsis models. Additionally, this compelling paper implies a concept that bacterial OMVs act as vehicles for the systemic distribution of ATP, influencing neutrophil activity and exacerbating sepsis severity.

Weaknesses:

(1) The researchers extracted and cultivated abdominal fluid on LB agar plates, then randomly picked 25 colonies for analysis. However, they didn't conduct 16S sequencing on the fluid itself. It's worth noting that the bacterial species present may vary depending on the individual patients. It would be beneficial if the authors could specify whether they've verified the existence of unculturable species capable of secreting high levels of Extracellular ATP.

(2) Do mice lacking commensal bacteria show a lack of Extracellular ATP following cecal ligation puncture?

(3) The authors isolated various bacteria from abdominal fluid, encompassing both Gram-negative and Gram-positive types. Nevertheless, their emphasis appeared to be primarily on the Gram-negative E. coli. It would be beneficial to ascertain whether the mechanisms of Extracellular ATP release differ between Gram-positive and Gram-negative bacteria. This is particularly relevant given that the Gram-positive bacterium E. faecalis, also isolated from the abdominal fluid, is recognized for its propensity to release substantial amounts of Extracellular ATP.

(4) The authors observed changes in the levels of LPM, SPM, and neutrophils in vivo. However, it remains uncertain whether the proliferation or migration of these cells is modulated or inhibited by ATP receptors like P2Y receptors. This aspect requires further investigation to establish a convincing connection.

(5) Additionally, is it possible that the observed in vivo changes could be triggered by bacterial components other than Extracellular ATP? In this research field, a comprehensive collection of inhibitors is available, so it is desirable to utilize them to demonstrate clearer results.

(6) Have the authors considered the role of host-derived Extracellular ATP in the context of inflammation?

(7) The authors mention that Extracellular ATP is rapidly hydrolyzed by ectonucleotases in vivo. Are the changes of immune cells within the peritoneal cavity caused by Extracellular ATP released from bacterial death or by OMVs?

(8) In the manuscript, the sample size (n) for the data consistently remains at 2. I would suggest expanding the sample size to enhance the robustness and rigor of the results.

eLife. 2024 Aug 20;13:RP96678. doi: 10.7554/eLife.96678.3.sa3

Author response

Daniel Spari ¹, Annina Schmid ², Daniel Sanchez-Taltavull ³, Shaira Murugan ⁴, Keely Keller ⁵, Nadia Ennaciri ⁶, Lilian Salm ⁷, Deborah Stroka ⁸, Guido Beldi ⁹

The following is the authors’ response to the original reviews.

The points raised let us critically rethink our approach, our results, and our conclusions. Furthermore, it gave us the chance to elaborate on some critical aspects that were mentioned. With the help of the reviewers, we made some clarifications in the point-by-point responses and implemented them in the manuscript. Furthermore, we modified the figures as suggested:

- The colors in Figure 1C, D, G and H have been adapted as suggested

- We added a Figure2-figure supplement 1, which strengthens our conclusion in Figure 2

- As asked by reviewer #1 (weaknesses #3), we added the data about neutrophil numbers in the different organs (Figure 6-figure supplement 3C).

Reviewer #1 (Public Review):

Summary:

- Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated with a reduction of peritoneal macrophages and CX3CR1+ monocytes, and an increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting that this mechanism could contribute to sepsis severity.

Strengths:

- A strong part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be relevant during systemic dissemination of bacteria in the host.

We want to thank the reviewer for recognizing this important aspect of our experimental approach.

Weaknesses:

- As pointed out in the limitations of the study whether ATP-loaded OMVs provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differentially induced by apyrase-expressing vs control E. coli transformants.

We thank the reviewer for raising several important points. In our study, we assessed local and systemic effects of released bacterial ATP. The consequences of local bacterial ATP release were assessed using an apyrase-expressing E. coli transformant. Locally, bacterial ATP resulted in a decrease in neutrophil numbers and we hypothesize that directly released bacterial ATP either leads to neutrophil death (e.g. via P2X7 receptor (Proietti et al., 2019)) or interferes with the recruitment of neutrophils (e.g. via P2Y receptors (Junger, 2011)).

The systemic consequences were assessed using ATP-loaded and empty OMV. We have shown that degranulation is induced by OMV-derived bacterial ATP. ATP-containing OMV are engulfed by neutrophils, reach its endolysosomal compartment and might activate purinergic receptors, which then lead to aberrant degranulation. This concept, that needs to be explored in future studies, is fundamentally different from classical purinergic signaling via directly released bacterial ATP into the extracellular space.

It is possible that neutrophil degranulation is also modulated by directly released bacterial ATP. We agree that this should be assessed in future studies. Also, the role of OMV-derived bacterial ATP should be assessed locally as well as the importance of directly released vs. OMV-mediated bacterial ATP dissected locally. Based on our measurements (Figure 4-figure supplement 1A and Figure 5C), we estimate that the effect of OMV-derived bacterial ATP might be much smaller than the effects of directly released bacterial ATP. Thus, direct ATP release might predominate locally. However, we fully agree that this has to be investigated in a future study to reconcile the different aspects of bacterial ATP signaling. A paragraph will be added to the manuscript, in which we discuss this particular issue.

- Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcomes than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs.

We fully acknowledge the mentioned discrepancy. What we propose is that bacterial ATP exhibits different functions that are dependent on the release mechanism (see above). Locally, in the peritoneal cavity, neutrophil numbers are decreased by directly released bacterial ATP. Remotely, ATP is delivered via OMV and impacts on neutrophil function. We agree that, in particular, in the peritoneal cavity, both effects may play a role. However, the impact of directly released bacterial ATP seems to be dominant (see above).

We propose that neutrophils are decreased locally because of directly released bacterial ATP, which prevents efficient infection control and, therefore, impairs sepsis survival. In addition, these fewer neutrophils might even be dysregulated by the engulfment of bacterial ATP delivered via OMV, which leads to an upregulated and possibly aberrant degranulation process worsening local and remote tissue damage. We agree that in addition to neutrophil numbers, the function of local neutrophils should be assessed with and without the influence of OMV-delivered bacterial ATP. This could be done by RNA sequencing of primary neutrophils from the peritoneal cavity or neutrophil cell lines as well as degranulation assays.

- Are the neutrophils counts affected by ATP delivered via OMVs?

This is difficult to show in the peritoneal cavity where we have both, directly released bacterial ATP and OMV-derived bacterial ATP. We assessed such putative difference, however, for the systemic organs and the blood, where we did not find any differences in neutrophil numbers.

- A comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP. The analyses performed on OMV treated versus E. coli infected mice are not closely related and difficult to combine when trying to draw a hypothesis for bacterial ATP in sepsis.

We fully agree that there are several open questions that remain to be elucidated, in particular, to differentiate the local role of directly released versus OMV-delivered bacterial ATP. In this study, we laid the foundation for future in vivo research to examine the specific role of bacterial ATP in sepsis. Such future research avenues might be to investigate the local effects of OMV-delivered bacterial ATP, and how neutrophil migration, apoptosis and degranulation are altered. We agree that exploration of the local secretory immune response and cytokine profiles are relevant to understand the different mechanisms of how bacterial ATP alters sepsis. However, such experiments should be ideally performed in systems where the source and the delivery of ATP can be modulated locally.

- Also it was not clear why lung neutrophils were used for the RNAseq data generation and analysis.

Thank you for this remark. We have chosen primary lung neutrophils for four reasons:

(1) Isolation of primary lung neutrophils allowed us to assess an in vivo response that would not have been possible with cell lines.

(2) The lung and the respiratory system are among the clinically most important organs affected during sepsis resulting in a significant cause of mortality.

(3) We show in Figure 6C that specifically in the lung, OMV are engulfed by neutrophils, which shows the relevance of the lung also in our study context.

(4) And finally, lung neutrophils were chosen to examine specifically distant and not local effects.

Reviewer #2 (Public Review):

Summary:

- In their manuscript "Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis", Daniel Spari et al. explored the dual role of ATP in exacerbating sepsis, revealing that ATP from both host and bacteria significantly impacts immune responses and disease progression.

Strengths:

- The study meticulously examines the complex relationship between ATP release and bacterial growth, membrane integrity, and how bacterial ATP potentially dampens inflammatory responses, thereby impairing survival in sepsis models. Additionally, this compelling paper implies a concept that bacterial OMVs act as vehicles for the systemic distribution of ATP, influencing neutrophil activity and exacerbating sepsis severity.

We thank the reviewer for mentioning these key points and supporting the relevance of our study.

Weaknesses:

(1) The researchers extracted and cultivated abdominal fluid on LB agar plates, then randomly picked 25 colonies for analysis. However, they did not conduct 16S rRNA gene amplicon sequencing on the fluid itself. It is worth noting that the bacterial species present may vary depending on the individual patients. It would be beneficial if the authors could specify whether they've verified the existence of unculturable species capable of secreting high levels of Extracellular ATP.

Most septic complications are caused by a limited spectrum of bacteria, belonging mainly either to the Firmicutes or the Proteobacteria phyla, including E. coli, K. pneumoniae, S. aureus or E. faecalis (Diekema et al., 2019; Mureșan et al., 2018). We validated this well documented existing evidence by randomly assessing 25 colonies. For the planned experiments, it was crucial to work with culturable bacteria; otherwise, ATP measurements, the modulation of ATP generation or loading of OMV would not have been possible. Using such culturable bacteria allowed us to describe mechanisms of ATP release.

We fully agree that hard-to-culture or unculturable bacteria might contribute significantly to septic complications. This, however, would need to be explored in future studies using extensive culturing methods (Cheng et al., 2022).

(2) Do mice lacking commensal bacteria show a lack of extracellular ATP following cecal ligation puncture?

ATP is typically secreted by many cells of the host in active and passive manners in the case of any injury, including cecal ligation and puncture (Burnstock, 2016; Dosch et al., 2018; Eltzschig et al., 2012; Idzko et al., 2014). We hypothesize that bacterial ATP is a potential priming agent at early stages of sepsis, and indeed, at such early time points, a comparison of peritoneal ATP levels between germfree and colonized mice could support our hypothesis. Future studies addressing this question must, however, correct for the different immune responses between germ-free and colonized mice. This is of utmost importance, especially for the cecal ligation and puncture model, since the cecum of germ-free mice is extremely large, making such experiments hard to control.

(3) The authors isolated various bacteria from abdominal fluid, encompassing both Gram-negative and Gram-positive types. Nevertheless, their emphasis appeared to be primarily on the Gram-negative E. coli. It would be beneficial to ascertain whether the mechanisms of Extracellular ATP release differ between Gram-positive and Gram-negative bacteria. This is particularly relevant given that the Gram-positive bacterium E. faecalis, also isolated from the abdominal fluid, is recognized for its propensity to release substantial amounts of Extracellular ATP.

We fully agree with this comment. In this paper, we used E. coli as our model organism to determine the principles of sepsis-associated bacterial ATP release and therefore focused on gram-negative bacteria. In addition to the direct, growth-dependent release, we found a relevant impact of OMV-delivered bacterial ATP. For this latter purpose, a gram-negative strain, in which OMV generation has been well described (Schwechheimer & Kuehn, 2015), was chosen. Recently, gram-positive bacteria have been shown to secrete ATP and OMV as well (Briaud & Carroll, 2020; Hironaka et al., 2013; Iwase et al., 2010). Given the fundamental differences in the structure of the cell wall of gram-positive bacteria and the mechanisms of OMV generation and release, future studies are required to assess the relevance of directly released and OMV-delivered ATP in gram-positive bacteria.

(4) The authors observed changes in the levels of LPM, SPM, and neutrophils in vivo. However, it remains uncertain whether the proliferation or migration of these cells is modulated or inhibited by ATP receptors like P2Y receptors. This aspect requires further investigation to establish a convincing connection.

We fully agree with this comment. The decrease in LPM and the consequential predomination of SPM have been well described after inflammatory stimuli in the context of the macrophage disappearance reaction (Ghosn et al., 2010). Also, it has been shown that purinergic signaling modulates infiltration of neutrophils and can lead to cell death as a consequence of P2Y and P2X receptor activation (Junger, 2011; Proietti et al., 2019). In our study, we propose that intracellular purinergic receptors contribute to neutrophil function during sepsis. After introducing the general principles and fundaments of bacterial ATP with our studies, we fully agree that additional experiments need to address downstream purinergic receptor activation. That, however, would go beyond the scope of our study.

(5) Additionally, is it possible that the observed in vivo changes could be triggered by bacterial components other than Extracellular ATP? In this research field, a comprehensive collection of inhibitors is available, so it is desirable to utilize them to demonstrate clearer results.

This question is of utmost importance and defined the choice of our model and experimental approach. When we started the project, we used two different E. coli mutants that release low (ompC) and high (eaeH) amounts of ATP. However, the limitation of this approach is that these are different bacteria, which may also differ in the components they secrete or the surface proteins they express. We, therefore, decided against that approach. With the approach we finally used (same bacterium, just with and without ATP), we aimed to minimize the influence of non-ATP bacterial components.

(6) Have the authors considered the role of host-derived Extracellular ATP in the context of inflammation?

Yes, the role of host-derived extracellular ATP in inflammation and sepsis is well-established with contradictory results (Csóka et al., 2015; Ledderose et al., 2016). This conflicting data was the rationale to test the relevance of bacterial ATP. We suggest that bacterial ATP is essential in the early phase of sepsis when bacteria invade the sterile compartment and before efficient host response, including the eukaryotic release of ATP, is established.

(7) The authors mention that Extracellular ATP is rapidly hydrolyzed by ectonucleotases in vivo. Are the changes of immune cells within the peritoneal cavity caused by Extracellular ATP released from bacterial death or by OMVs?

This is a relevant question that was also asked by reviewer #1, and we answered it in detail above (weaknesses comment #1 and #2). From our ATP measurements (Figure 4-figure supplement 1A and Figure 5C), we conclude that locally, the role of directly released bacterial ATP (extracellular) predominates over OMV-derived bacterial ATP. Furthermore, the mechanisms between directly released and OMV-derived bacterial ATP (within OMV, engulfed and transported to the endolysosomal compartment) are different, and especially extracellular ATP has been described to lead to apoptosis via P2X7 signaling.

(8) In the manuscript, the sample size (n) for the data consistently remains at 2. I would suggest expanding the sample size to enhance the robustness and rigor of the results.

Two biological replicates (independent cultures) were only used for the bacteria cultures in Figure 1, Figure 2, and Figure 3, which achieved similar results and the standard deviation remained very small, indicating its robustness. In the in vitro experiments in Figure 5 we used a sample size of 6 (three biological replicates measured in technical duplicates), since we saw bigger deviations in our measurements. For the in vivo experiments, we always used 5 or more animals in at least two independent experiments.

Reviewer #2 (Recommendations For The Authors):

(9). Line 37: 11 million sepsis-related deaths were reported "in" 2017.

The passage has been corrected as suggested.

(10) By the way, the similar colors used in Figure 1C and G are too chaotic, making it difficult to distinguish.

We agree, the colors have been adapted.

(11). All "in vivo" and "in vitro" should be italicized.

We italicized all of them.

(12). The title of Figure 4 is confusing: "Impairs sepsis outcome in vivo?" Could you make it more specific?

We agree, the title has been rephrased:

“Bacterial ATP reduces neutrophil counts and reduces survival in a mouse model of abdominal sepsis.”

(13) Line 314-316: The sentence "Potentially, despite the lack of a transporter, ATP may similarly to eukaryotic cells leak (Yegutkin et al., 2006) across the inner membrane into the periplasmic space that lacks the enzymes for ATP generation." sounds odd.

This passage was reformulated in the manuscript.

“Despite the lack of a transporter, ATP may leak across the inner membrane into the periplasmic space. Such leakage may be similar to baseline leakage in eukaryotic cells (Yegutkin et al., 2006).”

(14) The numerical notation in the paper is odd: sometimes it uses a prime symbol as a superscript (such as line 504), and sometimes it does not (such as line 421). Should it be standardized to "3,200" and "150,000"?

Thank you for this remark. The numbers have been standardized throughout the manuscript.

(15) Line "0.4 mm EP cuvettes" should be "0.4 cm EP cuvettes"

The specified passage has been corrected as suggested.

References

Briaud, P., & Carroll, R. K. (2020). Extracellular Vesicle Biogenesis and Functions in Gram-Positive Bacteria. Infection and Immunity, 88(12), 10.1128/iai.00433-20. https://doi.org/10.1128/iai.00433-20

Burnstock, G. (2016). P2X ion channel receptors and inflammation. Purinergic Signalling, 12(1), 59–67. https://doi.org/10.1007/s11302-015-9493-0

Cheng, A. G., Ho, P.-Y., Aranda-Díaz, A., Jain, S., Yu, F. B., Meng, X., Wang, M., Iakiviak, M., Nagashima, K., Zhao, A., Murugkar, P., Patil, A., Atabakhsh, K., Weakley, A., Yan, J., Brumbaugh, A. R., Higginbottom, S., Dimas, A., Shiver, A. L., … Fischbach, M. A. (2022). Design, construction, and in vivo augmentation of a complex gut microbiome. Cell, 185(19), 3617-3636.e19. https://doi.org/10.1016/j.cell.2022.08.003

Csóka, B., Németh, Z. H., Törő, G., Idzko, M., Zech, A., Koscsó, B., Spolarics, Z., Antonioli, L., Cseri, K., Erdélyi, K., Pacher, P., & Haskó, G. (2015). Extracellular ATP protects against sepsis through macrophage P2X7 purinergic receptors by enhancing intracellular bacterial killing. The FASEB Journal, 29(9), 3626–3637. https://doi.org/10.1096/fj.15-272450

Diekema, D. J., Hsueh, P.-R., Mendes, R. E., Pfaller, M. A., Rolston, K. V., Sader, H. S., & Jones, R. N. (2019). The Microbiology of Bloodstream Infection: 20-Year Trends from the SENTRY Antimicrobial Surveillance Program. Antimicrobial Agents and Chemotherapy, 63(7), e00355-19. https://doi.org/10.1128/AAC.00355-19

Dosch, M., Gerber, J., Jebbawi, F., & Beldi, G. (2018). Mechanisms of ATP Release by Inflammatory Cells. International Journal of Molecular Sciences, 19(4), 1222. https://doi.org/10.3390/ijms19041222

Eltzschig, H. K., Sitkovsky, M. V., & Robson, S. C. (2012). Purinergic Signaling during Inflammation. New England Journal of Medicine, 367(24), 2322–2333. https://doi.org/10.1056/NEJMra1205750

Ghosn, E. E. B., Cassado, A. A., Govoni, G. R., Fukuhara, T., Yang, Y., Monack, D. M., Bortoluci, K. R., Almeida, S. R., Herzenberg, L. A., & Herzenberg, L. A. (2010). Two physically, functionally, and developmentally distinct peritoneal macrophage subsets. Proceedings of the National Academy of Sciences, 107(6), 2568–2573. https://doi.org/10.1073/pnas.0915000107

Hironaka, I., Iwase, T., Sugimoto, S., Okuda, K., Tajima, A., Yanaga, K., & Mizunoe, Y. (2013). Glucose Triggers ATP Secretion from Bacteria in a Growth-Phase-Dependent Manner. Applied and Environmental Microbiology, 79(7), 2328–2335. https://doi.org/10.1128/AEM.03871-12

Idzko, M., Ferrari, D., & Eltzschig, H. K. (2014). Nucleotide signalling during inflammation. Nature, 509(7500), 310–317. https://doi.org/10.1038/nature13085

Iwase, T., Shinji, H., Tajima, A., Sato, F., Tamura, T., Iwamoto, T., Yoneda, M., & Mizunoe, Y. (2010). Isolation and Identification of ATP-Secreting Bacteria from Mice and Humans. Journal of Clinical Microbiology, 48(5), 1949–1951. https://doi.org/10.1128/JCM.01941-09

Junger, W. G. (2011). Immune cell regulation by autocrine purinergic signalling. Nature Reviews Immunology, 11(3), 201–212. https://doi.org/10.1038/nri2938

Ledderose, C., Bao, Y., Kondo, Y., Fakhari, M., Slubowski, C., Zhang, J., & Junger, W. G. (2016). Purinergic Signaling and the Immune Response in Sepsis: A Review. Clinical Therapeutics, 38(5), 1054–1065. https://doi.org/10.1016/j.clinthera.2016.04.002

Mureșan, M. G., Balmoș, I. A., Badea, I., & Santini, A. (2018). Abdominal Sepsis: An Update. The Journal of Critical Care Medicine, 4(4), 120–125. https://doi.org/10.2478/jccm-2018-0023

Proietti, M., Perruzza, L., Scribano, D., Pellegrini, G., D’Antuono, R., Strati, F., Raffaelli, M., Gonzalez, S. F., Thelen, M., Hardt, W.-D., Slack, E., Nicoletti, M., & Grassi, F. (2019). ATP released by intestinal bacteria limits the generation of protective IgA against enteropathogens. Nature Communications, 10(1), Article 1. https://doi.org/10.1038/s41467-018-08156-z

Schwechheimer, C., & Kuehn, M. J. (2015). Outer-membrane vesicles from Gram-negative bacteria: Biogenesis and functions. Nature Reviews Microbiology, 13(10), 605–619. https://doi.org/10.1038/nrmicro3525

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

Spari D, Schmid A, Sánchez-Taltavull D, Murugan S, Keller K, Ennaciri N, Salm L, Stroka D, Beldi G. 2024. Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis. NCBI Gene Expression Omnibus. GSE272296 [DOI] [PMC free article] [PubMed]
Beldi G, Keller KA, Sánchez Taltavull D, Murugan S, Schmid AB, Spari D, Ennaciri NS, Salm L, Keogh-Stroka DM. 2024. Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis. BORIS Portal. [DOI] [PMC free article] [PubMed]

Supplementary Materials

MDAR checklist

elife-96678-mdarchecklist1.pdf^{(228.1KB, pdf)}

Data Availability Statement

The following datasets were generated:

[bib1] Alvarez CL, Corradi G, Lauri N, Marginedas-Freixa I, Leal Denis MF, Enrique N, Mate SM, Milesi V, Ostuni MA, Herlax V, Schwarzbaum PJ. Dynamic regulation of extracellular ATP in Escherichia coli. The Biochemical Journal. 2017;474:1395–1416. doi: 10.1042/BCJ20160879. [DOI] [PubMed] [Google Scholar]

[bib2] Araujo MEG, Liebscher G, Hess MW, Huber LA. Lysosomal size matters. Traffic. 2020;21:60–75. doi: 10.1111/tra.12714. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib3] Arbizu PM. pairwiseAdonis. cb190f7GitHub. 2023 https://github.com/pmartinezarbizu/pairwiseAdonis

[bib4] Atarashi K, Nishimura J, Shima T, Umesaki Y, Yamamoto M, Onoue M, Yagita H, Ishii N, Evans R, Honda K, Takeda K. ATP drives lamina propria T(H)17 cell differentiation. Nature. 2008;455:808–812. doi: 10.1038/nature07240. [DOI] [PubMed] [Google Scholar]

[bib5] Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Molecular Systems Biology. 2006;2:2006.0008. doi: 10.1038/msb4100050. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib6] Babraham Bioinformatics FastQC A quality control tool for high throughput sequence data. Bioinformatics. 2024 http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

[bib7] Baeza N, Mercade E. Relationship between membrane vesicles, extracellular ATP and biofilm formation in antarctic gram-negative bacteria. Microbial Ecology. 2021;81:645–656. doi: 10.1007/s00248-020-01614-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib8] Bielaszewska M, Rüter C, Bauwens A, Greune L, Jarosch KA, Steil D, Zhang W, He X, Lloubes R, Fruth A, Kim KS, Schmidt MA, Dobrindt U, Mellmann A, Karch H. Host cell interactions of outer membrane vesicle-associated virulence factors of enterohemorrhagic Escherichia coli O157: Intracellular delivery, trafficking and mechanisms of cell injury. PLOS Pathogens. 2017;13:e1006159. doi: 10.1371/journal.ppat.1006159. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib9] Bittel M, Reichert P, Sarfati I, Dressel A, Leikam S, Uderhardt S, Stolzer I, Phu TA, Ng M, Vu NK, Tenzer S, Distler U, Wirtz S, Rothhammer V, Neurath MF, Raffai RL, Günther C, Momma S. Visualizing transfer of microbial biomolecules by outer membrane vesicles in microbe-host-communication in vivo. Journal of Extracellular Vesicles. 2021;10:e12159. doi: 10.1002/jev2.12159. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib10] Bitto NJ, Chapman R, Pidot S, Costin A, Lo C, Choi J, D’Cruze T, Reynolds EC, Dashper SG, Turnbull L, Whitchurch CB, Stinear TP, Stacey KJ, Ferrero RL. Bacterial membrane vesicles transport their DNA cargo into host cells. Scientific Reports. 2017;7:7072. doi: 10.1038/s41598-017-07288-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib11] Borisov VB, Gennis RB, Hemp J, Verkhovsky MI. The cytochrome bd respiratory oxygen reductases. Biochimica et Biophysica Acta. 2011;1807:1398–1413. doi: 10.1016/j.bbabio.2011.06.016. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib12] Burnstock G. In: Purinergic Signaling. Pelegrín P, editor. Springer; 2020. Introduction to purinergic signaling; pp. 1–15. [DOI] [PubMed] [Google Scholar]

[bib13] Cao M, Wang G, Xie J. Immune dysregulation in sepsis: experiences, lessons and perspectives. Cell Death Discovery. 2023;9:465. doi: 10.1038/s41420-023-01766-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib14] Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–i890. doi: 10.1093/bioinformatics/bty560. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib15] Choi U, Lee CR. Distinct roles of outer membrane porins in antibiotic resistance and membrane integrity in Escherichia coli. Frontiers in Microbiology. 2019;10:953. doi: 10.3389/fmicb.2019.00953. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib16] Diekema DJ, Hsueh PR, Mendes RE, Pfaller MA, Rolston KV, Sader HS, Jones RN. The microbiology of bloodstream infection: 20-year trends from the SENTRY antimicrobial surveillance program. Antimicrobial Agents and Chemotherapy. 2019;63:e00355-19. doi: 10.1128/AAC.00355-19. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib17] Ding Q, Quah SY, Tan KS. Secreted adenosine triphosphate from Aggregatibacter actinomycetemcomitans triggers chemokine response. Molecular Oral Microbiology. 2016a;31:423–434. doi: 10.1111/omi.12143. [DOI] [PubMed] [Google Scholar]

[bib18] Ding Q, Tan KS. The danger signal extracellular ATP is an inducer of Fusobacterium nucleatum biofilm dispersal. Frontiers in Cellular and Infection Microbiology. 2016b;6:155. doi: 10.3389/fcimb.2016.00155. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib19] Di Virgilio F, Sarti AC, Coutinho-Silva R. Purinergic signaling, DAMPs, and inflammation. American Journal of Physiology. Cell Physiology. 2020;318:C832–C835. doi: 10.1152/ajpcell.00053.2020. [DOI] [PubMed] [Google Scholar]

[bib20] Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21. doi: 10.1093/bioinformatics/bts635. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib21] Dosch M, Zindel J, Jebbawi F, Melin N, Sanchez-Taltavull D, Stroka D, Candinas D, Beldi G. Connexin-43-dependent ATP release mediates macrophage activation during sepsis. eLife. 2019;8:e42670. doi: 10.7554/eLife.42670. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib22] Eichelberger KR, Goldman WE. Manipulating neutrophil degranulation as a bacterial virulence strategy. PLOS Pathogens. 2020;16:e1009054. doi: 10.1371/journal.ppat.1009054. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib23] Eltzschig HK, Sitkovsky MV, Robson SC. Purinergic signaling during inflammation. The New England Journal of Medicine. 2012;367:2322–2333. doi: 10.1056/NEJMra1205750. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib24] Fu S, Wang Y, Xia X, Zheng JC. Exosome engineering: Current progress in cargo loading and targeted delivery. NanoImpact. 2020;20:100261. doi: 10.1016/j.impact.2020.100261. [DOI] [Google Scholar]

[bib25] Galber C, Carissimi S, Baracca A, Giorgio V. The ATP synthase deficiency in human diseases. Life. 2021;11:325. doi: 10.3390/life11040325. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib26] Gheinani AH, Vögeli M, Baumgartner U, Vassella E, Draeger A, Burkhard FC, Monastyrskaya K. Improved isolation strategies to increase the yield and purity of human urinary exosomes for biomarker discovery. Scientific Reports. 2018;8:3945. doi: 10.1038/s41598-018-22142-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib27] Ghosn EEB, Cassado AA, Govoni GR, Fukuhara T, Yang Y, Monack DM, Bortoluci KR, Almeida SR, Herzenberg LA, Herzenberg LA. Two physically, functionally, and developmentally distinct peritoneal macrophage subsets. PNAS. 2010;107:2568–2573. doi: 10.1073/pnas.0915000107. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib28] Grauel A, Kägi J, Rasmussen T, Makarchuk I, Oppermann S, Moumbock AFA, Wohlwend D, Müller R, Melin F, Günther S, Hellwig P, Böttcher B, Friedrich T. Structure of Escherichia coli cytochrome bd-II type oxidase with bound aurachin D. Nature Communications. 2021;12:6498. doi: 10.1038/s41467-021-26835-2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib29] Hironaka I, Iwase T, Sugimoto S, Okuda K, Tajima A, Yanaga K, Mizunoe Y. Glucose triggers ATP secretion from bacteria in a growth-phase-dependent manner. Applied and Environmental Microbiology. 2013;79:2328–2335. doi: 10.1128/AEM.03871-12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib30] Ihssen J, Jovanovic N, Sirec T, Spitz U. Real-time monitoring of extracellular ATP in bacterial cultures using thermostable luciferase. PLOS ONE. 2021;16:e0244200. doi: 10.1371/journal.pone.0244200. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib31] Ivancic V, Mastali M, Percy N, Gornbein J, Babbitt JT, Li Y, Landaw EM, Bruckner DA, Churchill BM, Haake DA. Rapid antimicrobial susceptibility determination of uropathogens in clinical urine specimens by use of ATP bioluminescence. Journal of Clinical Microbiology. 2008;46:1213–1219. doi: 10.1128/JCM.02036-07. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib32] Iwase T, Shinji H, Tajima A, Sato F, Tamura T, Iwamoto T, Yoneda M, Mizunoe Y. Isolation and identification of ATP-secreting bacteria from mice and humans. Journal of Clinical Microbiology. 2010;48:1949–1951. doi: 10.1128/JCM.01941-09. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib33] Jang SC, Kim SR, Yoon YJ, Park KS, Kim JH, Lee J, Kim OY, Choi EJ, Kim DK, Choi DS, Kim YK, Park J, Di Vizio D, Gho YS. In vivo kinetic biodistribution of nano-sized outer membrane vesicles derived from bacteria. Small. 2015;11:456–461. doi: 10.1002/smll.201401803. [DOI] [PubMed] [Google Scholar]

[bib34] Junger WG. Immune cell regulation by autocrine purinergic signalling. Nature Reviews. Immunology. 2011;11:201–212. doi: 10.1038/nri2938. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib35] Juodeikis R, Carding SR. Outer membrane vesicles: Biogenesis, functions, and issues. Microbiology and Molecular Biology Reviews. 2022;86:e0003222. doi: 10.1128/mmbr.00032-22. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib36] Kassambara A. Rstatix: pipe-friendly framework for basic statistical tests. 0.7.2R Packages. 2023 https://cran.r-project.org/web/packages/rstatix/index.html

[bib37] Kim JH, Yoon YJ, Lee J, Choi EJ, Yi N, Park KS, Park J, Lötvall J, Kim YK, Gho YS. Outer membrane vesicles derived from Escherichia coli up-regulate expression of endothelial cell adhesion molecules in vitro and in vivo. PLOS ONE. 2013;8:e59276. doi: 10.1371/journal.pone.0059276. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib38] Koch AL. Death of bacteria in growing culture. Journal of Bacteriology. 1959;77:623–629. doi: 10.1128/jb.77.5.623-629.1959. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib39] Kolberg L, Raudvere U. Gprofiler2: interface to the “g:profiler” toolset. 0.2.2R Packages. 2023 https://cran.r-project.org/web/packages/gprofiler2/index.html

[bib40] Kulp A, Kuehn MJ. Biological functions and biogenesis of secreted bacterial outer membrane vesicles. Annual Review of Microbiology. 2010;64:163–184. doi: 10.1146/annurev.micro.091208.073413. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib41] Ledderose C, Bao Y, Kondo Y, Fakhari M, Slubowski C, Zhang J, Junger WG. Purinergic signaling and the immune response in sepsis: A review. Clinical Therapeutics. 2016;38:1054–1065. doi: 10.1016/j.clinthera.2016.04.002. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib42] Leduc M, van Heijenoort J. Autolysis of Escherichia coli. Journal of Bacteriology. 1980;142:52–59. doi: 10.1128/jb.142.1.52-59.1980. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib43] Lee EY, Bang JY, Park GW, Choi DS, Kang JS, Kim HJ, Park KS, Lee JO, Kim YK, Kwon KH, Kim KP, Gho YS. Global proteomic profiling of native outer membrane vesicles derived from Escherichia coli. PROTEOMICS. 2007;7:3143–3153. doi: 10.1002/pmic.200700196. [DOI] [PubMed] [Google Scholar]

[bib44] Lee J, Yoon YJ, Kim JH, Dinh NTH, Go G, Tae S, Park KS, Park HT, Lee C, Roh TY, Di Vizio D, Gho YS. Outer membrane vesicles derived from Escherichia coli regulate neutrophil migration by induction of endothelial IL-8. Frontiers in Microbiology. 2018;9:2268. doi: 10.3389/fmicb.2018.02268. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib45] Leive L. Studies on the permeability change produced in coliform bacteria by ethylenediaminetetraacetate. The Journal of Biological Chemistry. 1968;243:2373–2380. [PubMed] [Google Scholar]

[bib46] Lennaárd AJ, Mamand DR, Wiklander RJ, El Andaloussi S, Wiklander OPB. Optimised electroporation for loading of extracellular vesicles with doxorubicin. Pharmaceutics. 2021;14:38. doi: 10.3390/pharmaceutics14010038. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib47] Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30:923–930. doi: 10.1093/bioinformatics/btt656. [DOI] [PubMed] [Google Scholar]

[bib48] Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology. 2014;15:550. doi: 10.1186/s13059-014-0550-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib49] Lundin A. In: Methods in Enzymology. Lundin A, editor. Elsevier; 2000. Use of firefly luciferase in atp-related assays of biomass, enzymes, and metabolites; pp. 346–370. [DOI] [PubMed] [Google Scholar]

[bib50] McBroom AJ, Johnson AP, Vemulapalli S, Kuehn MJ. Outer membrane vesicle production by Escherichia coli is independent of membrane instability. Journal of Bacteriology. 2006;188:5385–5392. doi: 10.1128/JB.00498-06. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib51] Mempin R, Tran H, Chen C, Gong H, Kim Ho K, Lu S. Release of extracellular ATP by bacteria during growth. BMC Microbiology. 2013;13:301. doi: 10.1186/1471-2180-13-301. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib52] Michel LV, Gaborski T. Outer membrane vesicles as molecular biomarkers for Gram-negative sepsis: Taking advantage of nature’s perfect packages. The Journal of Biological Chemistry. 2022;298:102483. doi: 10.1016/j.jbc.2022.102483. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib53] Mureșan MG, Balmoș IA, Badea I, Santini A. Abdominal sepsis: An update. The Journal of Critical Care Medicine. 2018;4:120–125. doi: 10.2478/jccm-2018-0023. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib54] Oksanen J, Simpson GL, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, Solymos P, Stevens MHH, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, Caceres MD, Durand S, Weedon J. Vegan: community ecology package. 2.6-4R Packages. 2022 https://cran.r-project.org/web/packages/vegan/index.html

[bib55] Orench-Rivera N, Kuehn MJ. Environmentally controlled bacterial vesicle-mediated export. Cellular Microbiology. 2016;18:1525–1536. doi: 10.1111/cmi.12676. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib56] Park KS, Choi KH, Kim YS, Hong BS, Kim OY, Kim JH, Yoon CM, Koh GY, Kim YK, Gho YS. Outer membrane vesicles derived from Escherichia coli induce systemic inflammatory response syndrome. PLOS ONE. 2010;5:e11334. doi: 10.1371/journal.pone.0011334. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib57] Park KS, Lee J, Jang SC, Kim SR, Jang MH, Lötvall J, Kim YK, Gho YS. Pulmonary inflammation induced by bacteria-free outer membrane vesicles from Pseudomonas aeruginosa. American Journal of Respiratory Cell and Molecular Biology. 2013;49:637–645. doi: 10.1165/rcmb.2012-0370OC. [DOI] [PubMed] [Google Scholar]

[bib58] Pérez-Cruz C, Carrión O, Delgado L, Martinez G, López-Iglesias C, Mercade E. New type of outer membrane vesicle produced by the Gram-negative bacterium Shewanella vesiculosa M7T: implications for DNA content. Applied and Environmental Microbiology. 2013;79:1874–1881. doi: 10.1128/AEM.03657-12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib59] Pérez-Cruz C, Delgado L, López-Iglesias C, Mercade E. Outer-inner membrane vesicles naturally secreted by gram-negative pathogenic bacteria. PLOS ONE. 2015;10:e0116896. doi: 10.1371/journal.pone.0116896. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib60] Perruzza L, Gargari G, Proietti M, Fosso B, D’Erchia AM, Faliti CE, Rezzonico-Jost T, Scribano D, Mauri L, Colombo D, Pellegrini G, Moregola A, Mooser C, Pesole G, Nicoletti M, Norata GD, Geuking MB, McCoy KD, Guglielmetti S, Grassi F. T follicular helper cells promote a beneficial gut ecosystem for host metabolic homeostasis by sensing microbiota-derived extracellular ATP. Cell Reports. 2017;18:2566–2575. doi: 10.1016/j.celrep.2017.02.061. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib61] Proietti M, Perruzza L, Scribano D, Pellegrini G, D’Antuono R, Strati F, Raffaelli M, Gonzalez SF, Thelen M, Hardt WD, Slack E, Nicoletti M, Grassi F. ATP released by intestinal bacteria limits the generation of protective IgA against enteropathogens. Nature Communications. 2019;10:250. doi: 10.1038/s41467-018-08156-z. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib62] Qureshi OS, Paramasivam A, Yu JCH, Murrell-Lagnado RD. Regulation of P2X4 receptors by lysosomal targeting, glycan protection and exocytosis. Journal of Cell Science. 2007;120:3838–3849. doi: 10.1242/jcs.010348. [DOI] [PubMed] [Google Scholar]

[bib63] Ray A, Dittel BN. Isolation of mouse peritoneal cavity cells. Journal of Visualized Experiments. 2010;35:1488. doi: 10.3791/1488. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib64] Reimer SL, Beniac DR, Hiebert SL, Booth TF, Chong PM, Westmacott GR, Zhanel GG, Bay DC. Comparative analysis of outer membrane vesicle isolation methods with an Escherichia coli tolA mutant reveals a hypervesiculating phenotype with outer-inner membrane vesicle content. Frontiers in Microbiology. 2021;12:628801. doi: 10.3389/fmicb.2021.628801. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib65] Reinhart K, Daniels R, Kissoon N, Machado FR, Schachter RD, Finfer S. Recognizing sepsis as a global health priority - A WHO resolution. The New England Journal of Medicine. 2017;377:414–417. doi: 10.1056/NEJMp1707170. [DOI] [PubMed] [Google Scholar]

[bib66] Rittirsch D, Huber-Lang MS, Flierl MA, Ward PA. Immunodesign of experimental sepsis by cecal ligation and puncture. Nature Protocols. 2009;4:31–36. doi: 10.1038/nprot.2008.214. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib67] Robinson LE, Murrell-Lagnado RD. The trafficking and targeting of P2X receptors. Frontiers in Cellular Neuroscience. 2013;7:233. doi: 10.3389/fncel.2013.00233. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib68] Ross N, Rudis B, Filipovic-Pierucci A, Galili T, Greenwell C. sjmgarnier/viridis: viridis 0.6.0 (pre-CRAN release) v0.6.0preZenodo. 2021 doi: 10.5281/zenodo.4679424. [DOI]

[bib69] Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, Colombara DV, Ikuta KS, Kissoon N, Finfer S, Fleischmann-Struzek C, Machado FR, Reinhart KK, Rowan K, Seymour CW, Watson RS, West TE, Marinho F, Hay SI, Lozano R, Lopez AD, Angus DC, Murray CJL, Naghavi M. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. The Lancet. 2020;395:200–211. doi: 10.1016/S0140-6736(19)32989-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib70] Salm L, Shim R, Noskovicova N, Kubes P. Gata6+ large peritoneal macrophages: an evolutionarily conserved sentinel and effector system for infection and injury. Trends in Immunology. 2023;44:129–145. doi: 10.1016/j.it.2022.12.002. [DOI] [PubMed] [Google Scholar]

[bib71] Santapaola D, Del Chierico F, Petrucca A, Uzzau S, Casalino M, Colonna B, Sessa R, Berlutti F, Nicoletti M. Apyrase, the product of the virulence plasmid-encoded phoN2 (apy) gene of Shigella flexneri, is necessary for proper unipolar IcsA localization and for efficient intercellular spread. Journal of Bacteriology. 2006;188:1620–1627. doi: 10.1128/JB.188.4.1620-1627.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib72] Schwechheimer C, Kuehn MJ. Outer-membrane vesicles from Gram-negative bacteria: biogenesis and functions. Nature Reviews. Microbiology. 2015;13:605–619. doi: 10.1038/nrmicro3525. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib73] Scribano D, Petrucca A, Pompili M, Ambrosi C, Bruni E, Zagaglia C, Prosseda G, Nencioni L, Casalino M, Polticelli F, Nicoletti M. Polar localization of PhoN2, a periplasmic virulence-associated factor of Shigella flexneri, is required for proper IcsA exposition at the old bacterial pole. PLOS ONE. 2014;9:e90230. doi: 10.1371/journal.pone.0090230. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib74] Slowikowski K, Schep A, Hughes S, Dang TK, Lukauskas S, Irisson JO, Kamvar ZN, Ryan T, Christophe D, Hiroaki Y, Gramme P, Abdol AM, Barrett M, Cannoodt R, Krassowski M, Chirico M, Aphalo P, Barton F. Ggrepel: automatically position non-overlapping text labels with “ggplot2.”. 0.9.5R Packages. 2023 https://cran.r-project.org/web/packages/ggrepel/index.html

[bib75] Spari D, Beldi G. Extracellular ATP as an inter-kingdom signaling molecule: Release Mechanisms by bacteria and its implication on the host. International Journal of Molecular Sciences. 2020;21:5590. doi: 10.3390/ijms21155590. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib76] Takaki K, Tahara YO, Nakamichi N, Hasegawa Y, Shintani M, Ohkuma M, Miyata M, Futamata H, Tashiro Y. Multilamellar and multivesicular outer membrane vesicles produced by a buttiauxella agrestis tolB Mutant. Applied and Environmental Microbiology. 2020;86:e01131-20. doi: 10.1128/AEM.01131-20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib77] Toyofuku M, Nomura N, Eberl L. Types and origins of bacterial membrane vesicles. Nature Reviews. Microbiology. 2019;17:13–24. doi: 10.1038/s41579-018-0112-2. [DOI] [PubMed] [Google Scholar]

[bib78] Tsubaki M, Hori H, Mogi T. Probing molecular structure of dioxygen reduction site of bacterial quinol oxidases through ligand binding to the redox metal centers. Journal of Inorganic Biochemistry. 2000;82:19–25. doi: 10.1016/s0162-0134(00)00140-9. [DOI] [PubMed] [Google Scholar]

[bib79] Turnbull L, Toyofuku M, Hynen AL, Kurosawa M, Pessi G, Petty NK, Osvath SR, Cárcamo-Oyarce G, Gloag ES, Shimoni R, Omasits U, Ito S, Yap X, Monahan LG, Cavaliere R, Ahrens CH, Charles IG, Nomura N, Eberl L, Whitchurch CB. Explosive cell lysis as a mechanism for the biogenesis of bacterial membrane vesicles and biofilms. Nature Communications. 2016;7:11220. doi: 10.1038/ncomms11220. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib80] Turner L, Praszkier J, Hutton ML, Steer D, Ramm G, Kaparakis-Liaskos M, Ferrero RL. Increased outer membrane vesicle formation in a Helicobacter pylori tolB mutant. Helicobacter. 2015;20:269–283. doi: 10.1111/hel.12196. [DOI] [PubMed] [Google Scholar]

[bib81] Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, Saeys Y. FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data. Cytometry. Part A. 2015;87:636–645. doi: 10.1002/cyto.a.22625. [DOI] [PubMed] [Google Scholar]

[bib82] Vega-Pérez A, Villarrubia LH, Godio C, Gutiérrez-González A, Feo-Lucas L, Ferriz M, Martínez-Puente N, Alcaín J, Mora A, Sabio G, López-Bravo M, Ardavín C. Resident macrophage-dependent immune cell scaffolds drive anti-bacterial defense in the peritoneal cavity. Immunity. 2021;54:2578–2594. doi: 10.1016/j.immuni.2021.10.007. [DOI] [PubMed] [Google Scholar]

[bib83] Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W, Liaw A, Lumley T, Maechler M, Magnusson A, Moeller S, Schwartz M, Venables B, Galili T. Gplots: various R programming tools for plotting data. 3.1.3R Packages. 2022 https://cran.r-project.org/web/packages/gplots/index.html

[bib84] Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 16S ribosomal DNA amplification for phylogenetic study. Journal of Bacteriology. 1991;173:697–703. doi: 10.1128/jb.173.2.697-703.1991. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib85] Wickham H. Ggplot2. Springer International Publishing; 2016. [DOI] [Google Scholar]

[bib86] Wickham H, Bryan J. readxl: Read Excel Files. 1.4.3R Packages. 2023a https://cran.r-project.org/web/packages/readxl/index.html

[bib87] Wickham H, François R, Henry L, Müller K. Dplyr: A grammar of data manipulation. 1.1.4R Packages. 2023b https://cran.r-project.org/web/packages/dplyr/index.html

[bib88] Xu S, Chen M, Feng T, Zhan L, Zhou L, Yu G. Use ggbreak to effectively utilize plotting space to deal with large datasets and outliers. Frontiers in Genetics. 2021;12:774846. doi: 10.3389/fgene.2021.774846. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib89] Yamamoto N, Nakahigashi K, Nakamichi T, Yoshino M, Takai Y, Touda Y, Furubayashi A, Kinjyo S, Dose H, Hasegawa M, Datsenko KA, Nakayashiki T, Tomita M, Wanner BL, Mori H. Update on the Keio collection of Escherichia coli single-gene deletion mutants. Molecular Systems Biology. 2009;5:335. doi: 10.1038/msb.2009.92. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib90] Yegutkin GG, Mikhailov A, Samburski SS, Jalkanen S. The detection of micromolar pericellular ATP pool on lymphocyte surface by using lymphoid ecto-adenylate kinase as intrinsic ATP sensor. Molecular Biology of the Cell. 2006;17:3378–3385. doi: 10.1091/mbc.e05-10-0993. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib91] Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nature Communications. 2019;10:1523. doi: 10.1038/s41467-019-09234-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib92] Zindel J, Peiseler M, Hossain M, Deppermann C, Lee WY, Haenni B, Zuber B, Deniset JF, Surewaard BGJ, Candinas D, Kubes P. Primordial GATA6 macrophages function as extravascular platelets in sterile injury. Science. 2021;371:eabe0595. doi: 10.1126/science.abe0595. [DOI] [PubMed] [Google Scholar]

PERMALINK

Released bacterial ATP shapes local and systemic inflammation during abdominal sepsis

Daniel Spari

Annina Schmid

Daniel Sanchez-Taltavull

Shaira Murugan

Keely Keller

Nadia Ennaciri

Lilian Salm

Deborah Stroka

Guido Beldi

Roles

Abstract

eLife digest

Introduction

Results

E. coli, one of the major pathogens in sepsis, releases ATP in a growth-dependent manner

Figure 1. Sepsis-associated bacteria release adenosine triphosphate (ATP) in a growth-dependent manner.

Figure 1—figure supplement 1. Experimental approach to measure released bacterial adenosine triphosphate (ATP) and growth over time.

Bacterial ATP release is dependent on ATP synthesis at the inner bacterial membrane and correlates with bacterial growth

Figure 2. Adenosine triphosphate (ATP) release is dependent on ATP synthesis.

Figure 2—figure supplement 1. Peak ATP (M) and peak growth (OD600*hours) of all assessed cyo and atp mutants and the PS were plotted against each other.

Outer bacterial membrane integrity and bacterial death determine bacterial ATP release during growth

Figure 3. Outer membrane integrity and bacterial death determine bacterial adenosine triphosphate (ATP) release during growth.

Released bacterial ATP reduces neutrophil counts and impairs survival during abdominal sepsis

Figure 4. Bacterial adenosine triphosphate (ATP) reduces neutrophil counts and impairs sepsis outcome in vivo.

Figure 4—figure supplement 1. Immune cell characterization 8 hr after intraabdominal (i.a.) injection of bacteria.

Establishing ATP-loaded OMV as a model system to assess the systemic relevance of bacterial ATP

Figure 5. Outer membrane vesicles (OMV) contain adenosine triphosphate (ATP) and can be exploited as a model to assess the systemic relevance of bacterial ATP.

Figure 5—figure supplement 1. Adenosine triphosphate (ATP) measurement of the parental strain (PS), ΔnlpI as well as ΔtolB and outer membrane vesicle (OMV) collection and characterization.

OMV-derived bacterial ATP induces degranulation processes in neutrophils after lysosomal uptake

Figure 6. Bacterial adenosine triphosphate (ATP) within outer membrane vesicles (OMV) upregulates lysosome-related pathways and degranulation processes in neutrophils.

Figure 6—figure supplement 1. Uptake of outer membrane vesicles (OMV) by neutrophils.

Figure 6—figure supplement 2. Characterization of local immune response in the abdominal cavity.

Figure 6—figure supplement 3. Assessment of outer membrane vesicle (OMV) uptake by immune cells in remote organs.

Figure 6—figure supplement 4. Assessment of the purity of bead-sorted pulmonary neutrophils.

Figure 6—figure supplement 5. List of significantly different pathways after enrichment analysis of RNA sequencing results.

Discussion

Materials and methods

Human data

Mouse handling

CLP sepsis model

Whole 16S-rRNA Sanger sequencing

Quantification of released bacterial ATP

Absolute quantification of bacteria and assessment of viability

Transformation of E. coli PS

Bacteria injection sepsis model

Collection of abdominal fluid, blood, and organs

Digestion of organs and preparation of single-cell suspension

Staining of cells and flow cytometry

Absolute quantification of bacteria by plating

Collection of OMV and ATP measurement of OMV

EP and staining of OMV

OMV injection sepsis model

Assessment of ATP release by OMV

SDS-PAGE, protein staining, and western blot

Nanoparticle tracking analysis

Electron microscopy negative staining

Immunofluorescent microscopy

RNA isolation from pulmonary neutrophils

RNA sequencing

Alignment and quantification

Data visualization

Differential gene expression

Pathway enrichment analysis

Heatmaps

Volcano plot

Statistical analysis

Acknowledgements

Appendix 1

Appendix 1—key resources table.

Funding Statement

Contributor Information

Funding Information

Additional information

Competing interests

Author contributions

Ethics

Additional files

Data availability

Figure 2—figure supplement 1. Peak ATP (M) and peak growth (OD₆₀₀*hours) of all assessed cyo and atp mutants and the PS were plotted against each other.