Proteomic and Metabolomic Profiling of Archaeal Extracellular Vesicles from the Human Gut

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However, the interactive mechanisms of members of the human archaeome remained largely unexplored. Here, we report the capability of two Methanobrevibacter strains M. smithii, Cand. M. intestini and Methanosphaera stadtmanae, to produce EVs. While the size (~ 130 nm) and morphology of these archaeal EVs were comparable to bacterial EVs, proteomic and metabolomic analyses revealed unique traits. The proteins found in both the EVs of M. smithii and Cand. M. intestini (n = 229) predominantly included adhesin and adhesin-like proteins, involved in archaea-surface and archaea-bacteria interaction. Additionally, the archaeal EVs contained glutamic acid and choline glycerophosphate, which could be involved in gut-brain signalling. Vesicles from all studied species were efficiently taken up by human monocytes and induced IL-8 production in epithelial HT-29 cells. The identification of archaeal EVs and their components provides novel insights into the complex interactions between the archaeal and bacterial microbiome and the host, potentially offering new paths to modulate vesicle-mediated impacts on host health. Biological sciences/Microbiology/Archaea/Archaeal biology Biological sciences/Biological techniques Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction All organisms have evolved various signaling mechanisms to convey crucial biological information across cells, tissues, and organs 1–3 . Among these mechanisms are extracellular vesicles (EVs), which are small membrane-bound spherical particles produced and released by cells of all three domains of life 1 . In the gastrointestinal tract (GIT), extracellular vesicles produced by commensal bacteria (bacterial extracellular vesicles, BEVs) mediate intra- and inter-kingdom interactions, maintaining the microbiome ecosystem and promoting interactions with the host 2 . BEVs have garnered considerable attention in recent years due to their diverse roles in intercellular communication, pathogenesis, stress tolerance, immune stimulation, and host-microbe interactions 3–7 . These small, membrane-bound structures serve as vehicles for the transport of biomolecules such as proteins, nucleic acids, metabolites and lipids between bacterial cells, as well as between bacteria and their host environments 4,8–12 . Understanding the mechanisms underlying BEV biogenesis, cargo loading, and their impact on microbial communities and host physiology is critical in microbiology and biomedical research 4 . BEVs are divided into different categories based on either their producing bacteria (BEVs from Gram-negative and Gram-positive bacteria) or their origin and the pathway by which they are formed (outer membrane vesicles, outer-inner membrane vesicles, explosive membrane vesicles or cytoplasmic membrane vesicles) 13,14 . Outer membrane vesicles (OMVs) are considered as the archetypal bacterial membrane vesicles. These OMVs usually arise from a protrusion of the outer membrane and their envelope, therefore resembling the envelope of the donor cell. They usually contain surface-associated factors, outer membrane proteins, and periplasmic content 13,14 . Explosive membrane vesicles on the other hand diversify BEV composition, explaining the presence of nucleic acids and cytosolic content in vesicle samples from Gram-negative bacteria. In the course of the last decade, it has become evident that BEVs of GIT-colonizing bacteria potentially influence essential functions of the intestine, and of systemic organs after their migration to the bloodstream, thereby contributing to host health 15 . For instance, BEVs contribute to host digestion by distributing hydrolase activities across the lumen, and can potentially influence the central nervous system following migration through the gut-brain axis 16 . Additionally, BEVs can act as efficient delivery vehicles of bioactive compounds, such as toxins or modulators of host cell physiology 13,14 . BEVs are recognized and efficiently internalized by various host cells resulting in intestinal barrier changes, immunomodulation and (patho-)physiological changes 13,14 . BEVs can also act on the surrounding microbiota, promoting bacterial colonization and growth as well as protecting bacteria from antibiotics and host defense peptides 11,17,18 . Triggers for vesicle formation are manifold, including factors such as media composition, growth phase, temperature, iron and oxygen availability, as well as exposure to antibiotics and stress 13,14 . As a consequence of the diverse triggers and various origins, the vesicle preparations likely reflect a mixture of different BEV types, which could explain variable BEV functions and effects, and experiments are sometimes non-conclusive 14 . Representatives of all three domains of eukaryotes, bacteria, and archaea, are capable of forming extracellular vesicles 19 . The reports on archaeal vesicles are overall fairly rare and are restricted to extremophilic archaea, namely Thermococcales and Sulfolobales. It appears that in Sulfolobus , for example, vesicle formation is evolutionarily related to eukaryotic ESCRT complex proteins used for the building of endosomes; however, other archaea, such as Thermococcus form vesicles but do lack the ESCRT complex, indicating a higher variety in vesicle formation mechanisms 19 . In general, a defensive function through these vesicles was proposed, but research is still ongoing 20 . However, archaea not only thrive in environmental ecosystems, but are also considered as reliable and prevalent constituents of the human GIT microbiome. With 1.2% relative abundance on average, Methanobrevibacter and Methanosphaera species are highly prevalent across individuals (> 90%) 21,22 . Trough maintaining numerous syntrophic relationships with intestinal bacteria, these archaea have the capacity to orchestrate the entire microbiome, leading to an optimized fibre degradation 23 . They also influence the host with respect to the provision of short chain fatty acids or mediate the reduction of gut motility, leading to constipation 18 . However, the mechanisms by which they interact with other microorganisms and their mode of signaling have remained unknown. In this manuscript, we focus on the recent discovery of archaeal extracellular vesicles (AEVs) produced by human archaeal representatives and present novel findings on their ultrastructure, proteome, and metabolome, as well as their interaction with human cell lines. We will discuss the implications of this discovery for our understanding of microbiome-host interactions and outline future directions for research. By integrating insights from bacterial and archaeal EV biology, we strive to unravel the complexities of microbial communication networks within the human body and their implications for health and disease. Results Vesicles produced by Methanobrevibacter intestini, M. smithii ALI, M. smithii GRAZ-2 and Methanosphaera stadtmanae were visualized by electron microscopy in supernatants of cultures in the late exponential/stationary phase. Using protocols developed and optimized for BEV analysis, AEV biomass production and an isolation protocol were established to enable characterization with respect to size, composition, ultrastructure, proteome, metabolome, and interaction with mammalian cells. AEV formation in all methanogen species Negative staining- and ultra-thin electron-microscopy- based methods revealed the presence of vesicle-like structures within (Fig. 1 F,I, J) and attached to the cells (Fig. 1 A, E, H, K) and in their close vicinity (Fig. 1 B) in all methanoarchaeal cultures. These were usually round shaped, approximately 87–198 nm in size (~ 130 nm on average, sizes measured during NTA, Fig. 1 C, D, G, L), and showed a clear, sharp edge. No vesicles were observed in culture media controls that also underwent microscopy imaging. Biophysical AEV characteristics AEVs from the methanogens M. smithii ALI, M. smithii GRAZ-2, M. intestini and M. stadtmanae were purified using a centrifugation, filtration and concentration pipeline, previously established for bacterial EVs 27 with minor adaptations (see materials and methods). To the former described BEV isolation protocol, a centrifugation step (10.000 x g, 20 min) was added to remove residues from the culture media. The basic characteristics of the AEVs (size, concentration, nucleic acid, protein and lipid content) are summarized in Table 1 and Fig. 2 . The size of the AEVs ranged from 86.9 to 197.3 nm (~ 130 nm on average). M. intestini derived AEVs were found to be the largest (~ 136 nm on average), and M. smithii GRAZ-2-derived vesicles the smallest (~ 117 nm), which were similar in size to those of M. smithii ALI (~ 124 nm). Overall the size of the vesicles was in the range of BEVs (20–400 nm) 3,57,58 e.g. from enterotoxigenic Escherichia coli (ETEC, ~ 120 nm), but slightly smaller than BEVs e.g. from Bacteroides thetaiotaomicron (~ 180 nm) 59 , and B. fragilis (~ 194 nm). Average concentration of the retrieved AEVs (Table 1 ) was much lower than concentrations usually measured for BEVs, such as ETEC (6.38E + 11 particles/ml), and B. fragilis (8E + 11 particles/ml). The concentrations were reasonably consistent for all M. smithii strains, with lower concentration retrieved for M. intestini and M. stadtmanae (Table 1 ). Overall, the protein content ranged from 0.09 to 180.6 µg/10 10 particles. On average, AEV extracts of M. smithii GRAZ-2 contained the highest protein concentration (~ 52 µg/10 10 particles), whereas the lowest concentrations were found in M. smithii ALI (~ 7.8 µg/10 10 particles). Regarding the lipid content, all AEVs extracts were in the range of the standard linoleic acid (20–100 µg/ml). AEVs from M. intestini showed the highest (~ 81.20 µg/10 10 particles) and the lowest amount of lipids (~ 4.9 µg/10 10 particles on average). It has to be mentioned that the lipid content could only be detected in a few samples, as not all measurements of concentrations were found in the standard range. Overall, the DNA content of AEV extracts ranged from 0.004 to 18.27 µg/10 10 particles. AEVs of M. intestini had the highest DNA concentration (3.14 µg/10 10 particles), while M. stadtmanae had the lowest one (0.55 µg/10 10 particles) on average. RNA content of AEVs could not be detected in all samples, due to low concentrations. AEVs from Methanobrevibacter strains contain similarly low amounts of RNA (0.08 − 0.014µg/10 10 particles), while 0.17 µg/10 10 particles could be detected for M. stadtmanae . Table 1 Summary of archaeal vesicles’ properties, namely size, concentration, protein, DNA, RNA, and lipid content. Protein, DNA, RNA, and lipid contents were normalized to µg/10 10 particles. Size [nm] Concentration [particles/ml] Protein [µg/10 10 particles] DNA [µg/10 10 particles] RNA [µg/10 10 particles] Lipid [µg/10 10 particles] M. smithii ALI Mean Min. Max. 123.61 86.90 148.00 2.16E + 11 1.21E + 10 2.33E + 12 7.76 0.26 16.32 0.84 0.04 4.72 0.08 0.04 0.19 4.87 1.75 10.90 M. intestini Mean Min. Max. 136.85 87.90 197.30 3.03E + 10 2.60E + 09 9.20E + 10 13.89 7.01 41.07 3.14 0.46 18.27 0.14 0.07 0.2 81.20 81.20 81.20 M. smithii GRAZ-2 Mean Min. Max. 117.28 91.30 138.90 3.69E + 11 1.20E + 10 5.63E + 12 51.78 0.09 180.63 0.63 0.004 1.28 0.14 0.001 0.28 11.00 11.00 11.00 M. stadtmanae Mean Min. Max. 127.92 94 168.70 1.44E + 10 4.20E + 09 4.08E + 10 16.62 5.93 37.33 0.55 0.01 2.56 0.17 0.17 0.17 35.30 35.30 35.30 Methanobrevibacter AEVs have comparable proteomes and show a massive enrichment in adhesins The protein cargo of M. smithii ALI and M. intestini EVs were compared with that of their respective whole microbial cell proteomes (whole cell lysate, WCL). Profiling was carried out through LC-MS/MS, employing isolated AEVs and whole cell lysates (n = 3) of M. smithii ALI and M. intestini (refer to material and methods section for details). A total of 1475 vesicular proteins across all isolated EVs were identified ( M. smithii ALI: 801; M. intestini: 674), complemented by the identification of 2537 proteins from the whole cell lysates (WCL; M. smithii ALI: 1262; M. intestini: 1275, Supplementary Fig. S3, Supplementary Table 1). Proteins were considered to be present in a sample, based on a prevalence in three out of three replicates for each group of sample (WCL M. smithii ALI (WCL_ALI): 1026; WCL M. intestini (WCL_int): 1100; EVs M. smithii ALI (EV_ALI): 364, and EVs M. intestini (EV_int): 259; Supplementary Fig. S2, Supplementary Table 1). Compared to the 2047 proteins identified in BEVs derived from B. thetaiotaomicron 59 , the total number of proteins in methanoarchaeal EVs was much lower. AEVs derived from M. smithii ALI (EV_ALI) and M. intestini (EV_int) share 229 proteins, while having 135 and 30 unique proteins in these strains, respectively (Fig. 3 B). Only a small number of proteins (EV_ALI: 35, EV_int: 56) were detected in the vesicles but not in the whole cell lysates (Fig. 3 D and E). Proteins of whole cell lysates were highly similar, as 816 proteins were identified in both WCL_ALI and WCL_int (Fig. 3 A). 173 proteins were found in all four groups (EV and WCL of both strains, Fig. 3 C). The PCA plot depicted in Fig. 4 A illustrates different distribution patterns between whole-cell lysates (WCL) and extracellular vesicles (EVs) for both strains. Notably, it also highlights the similarities observed between WCL_ALI and WCL_int, as well as between EV_ALI and EV_int. The protein content of the vesicles of both Methanobrevibacter species was strikingly similar (Fig. 4 , Supplementary Fig. S2 and S3), with 229 proteins found in all six extracts. The most abundant proteins were Adhesins/ adhesin-like proteins/ proteins with an IG-like domain, as identified through InterPro prediction (ALPs, Fig. 4 B and C; for details on functional annotation see Materials and Methods and Supplementary Table 6); these proteins were also highly enriched compared to the whole-cell lysates (WCL, Fig. 4 B and C; Supplementary Table 4) 47 . ALPs are rarely studied in archaea, but were found to be very abundant in e.g. rumen methanogens where they account for up to 5% of all genes. It has been suggested that the ALPs serve to attach to their protozoan hosts or to the cell surface of bacteria 62 . ALPs have also been found in human-associated Methanobrevibacter species 63 , for which adhesion and sugar-binding function has been proposed. Indeed, the identified vesicle-associated ALPs carried a variety of protein domains, indicative of an adhesive (Invasin/intimin cell-adhesion fragments; IG-like_fold superfamily) and polysaccharide binding functions (PbH1; pectin_lyase_fold, Pectin_lyase_fold/virulence; details for all genes and their identified domains are given in Supplementary Table 5). Bacterial proteins containing IG-like domains exhibit a broad spectrum of functions, such as cell host adhesion and invasion. IG-like domains are also found in periplasmic chaperones and proteins that assemble fimbriae, in oxidoreductases and hydrolytic enzymes, ATP-binding cassette transporters, sugar-binding and metal-resistant proteins 64 . These proteins are structural components of bacterial pilus and nonpilus fimbrial systems and members of the intimin/invasin family of outer membrane adhesins, indicating their relevance for adhesion and interaction with the biological surroundings. Microbial pectin and pectate lyases are involved in the degradation of pectic components of the plant cell, which is an important trait for plant pathogens, as well as the degradation of dietary components in the gastrointestinal tract. However, this specific β-helix topology has various functions e.g. as galacturonases, or for the adhesion to mammalian cells 65 . Within a group of transport-associated proteins, we found substantial enrichment of a protein (representative: GUT_GENOME043902_01504) with an OPT (oligopeptide transporter) superfamily domain, which in prokaryotes may contribute to iron-siderophore uptake 66 , indicating a potential role in iron binding. A further substantial increase was observed for a putative DUF11 domain-containing protein 67 , which might be important for stabilizing surface wall structures in Methanothermobacter sp. strain CaT2 67 . Another interesting finding was the increased presence of a putative peptidase_C1, which also showed adhesin-like domains (Supplementary Tables 4 and 6). Metabolite cargo of AEVs could have an effect on gut-brain-axis Similar to the proteomic analyses, the metabolic profiles of AEVs of M. smithii ALI and M. intestini were overall similar, but with high variability across biological replicates, probably due to variations in input concentrations (see group CV % in Supplementary Table 7; Fig. 4 ). Strikingly, the AEVs of M. intestini revealed a significantly increased content of glutamic and aspartic acid (Fig. 5 ; P = 0.03 and P = 0.01, respectively; Supplementary Table 7; this table also includes details on statistics). Also, the AEVs of M. smithii ALI revealed a substantial Log2 Fold Change (FC) compared to background samples, indicating that these amino acids are important cargos for both species. M. smithii ALI were substantially loaded with arginine. Notably, glutamate has been identified as a component of bacterial EVs ( B. fragilis) 68 . Besides their roles in central metabolism, both amino acids are considered to act as neurotransmitters 69 . Glutamate plays a fundamental role as an excitatory neurotransmitter in the central nervous and the enteric nervous system and acts, together with other metabolites, along the “microbiota-gut-brain axis” 70 as an “interkingdom communication system”. It is considered that the glutamatergic receptors, along the microbiota-gut-brain axis, could have an impact on multiple physiological responses in the brain and gut. As glutamate usually does not enter the bloodstream from the large intestine, AEVs could be supporting the transmission to glutamatergic enteric neurons/ receptors 70 . Despite its potential function as a neurotransmitter, aspartate also supports the proliferation of mammalian cells (e.g. cancer cells) 59 . Choline glycerophosphate (glycerophosphorylcholine, alpha GPC) was found to be elevated in AEVs of both species (Fig. 5 ). Also, for this compound, a potential neurological effect was described, which has been considered for the treatment of Alzheimer’s disease 71 . The origin of the salicylic acid, which was found to be increased in AEVs of both species, is unclear (potentially from chorismate), but its potential effects on the host and microbiome could include bactericidal and antiseptic action in higher concentrations 72 . Another compound found to be increased was oxalic acid, the latter having the characteristics of a chelating agent for metal cations, making insoluble iron compounds into a soluble complex ion, which could be an interesting trait for gastrointestinal microbiota 73 . Human monocytes acquire AEVs Human leukemia monocytic THP-1 cells are a common model for studying monocyte/macrophage functions, signaling pathways, mechanisms, and drug and nutrient transport 74 . For visualizing the association or interaction of AEVs with host cells, AEVs of M. smithii ALI, M. smithii GRAZ-2, M. intestini, and M. stadtmanae were incubated with macrophage monolayers (THP1-b) for 24 h and their localization was assessed by immunofluorescence microscopy. Co-localization of DiO-labeled AEVs (Fig. 6 A-E, green dye) with and within host cell nuclei were investigated using the nuclei marker Hoechst 33342 (blue), and the cytoskeleton marker Alexa 647-Phalloidin (red). AEVs from all strains were shown to be in close association with the nuclei. Similar localization of EVs was previously described for bacterial EVs e.g. from B. thetaiotaomicron 75 . A representative z-stack of M. stadtmanae AEVs and macrophage monolayers supports the uptake of AEVs by the macrophage cells (Fig. 6 E). AEVs of M. intestini induce substantial IL-8 excretion in HT29 epithelial cell line Human intestinal HT-29 cells are useful for epithelial cell research, and have recently been used in a comparative study to assess the differential pro-inflammatory potency of BEVs derived from gut bacteria 25 . To investigate the pro-inflammatory potential of AEVs, we examined the IL-8 cytokine response in intestinal epithelial cells upon exposure to AEVs derived from M. smithii ALI, M. smithii GRAZ-2, M. intestini, and M. stadtmanae . The pro-inflammatory cytokine IL-8 was chosen as it demonstrated a robust BEV-dependent induction in a previous study 25 . Moreover, BEVs of enterotoxigenic Escherichia coli (ETEC) and B. fragilis were included as representatives of intestinal BEVs known to induce a very high or no IL-8 response 25 . In concordance to a recent report 76 , AEVs derived from M. smithii ALI, M. smithii GRAZ-2, and M. stadtmanae failed to induce a significant increase of the IL-8 levels compared to the no treatment control (NTC, P > 0.05, Fig. 7 ). In contrast, exposure of HT-29 cells to AEVs derived from M. intestini resulted in a significant IL-8 induction ( P < 0.001) at similar levels as observed for BEVs from ETEC ( P < 0.001). These results suggest that AEVs derived from different archaeal species demonstrate differential pro-inflammatory potency in HT-29 cells with AEVs from M. intestini inducing a relatively strong IL-8 response. Discussion The discovery of archaeal extracellular vesicles (AEVs) produced by human GIT-associated archaea introduces a novel principle in archaea-microbiota and archaea-host interactions. Just like bacterial extracellular vesicles (BEVs) known from the human gut microbiota, AEVs are membrane-bound structures that transport various biomolecules, including proteins, lipids, and nucleic acids 4,8–12 . We assume that these vesicles as well, have the potential to modulate the microbial community and host physiology, by acting as a communication and cargo vehicle. This study demonstrates that AEVs derived from GIT-associated archaea are comparable in size to BEVs, although the particle count was substantially lower for archaea (Fig. 2 , Table 1 ). Previous research has indicated that growth conditions, such as growth stage and medium composition, can influence the particle count, size, and vesicle cargo of BEVs leading to a heterogeneity among BEVs 13,29,77–82 . It is likely that similar effects occur with AEVs. As we used biological replicates in our experiments, a certain fluctuation in e.g. metabolite cargo was observed. Heterogeneity implies that different vesicle subtypes may carry distinct cargo, potentially leading to varied biological effects by targeting different host cells or microbial cells 83–85 . Moreover, the isolation process itself might impact the retrieval of different vesicle subtypes 83 . Both studied archaeal genera ( Methanobrevibacter and Methanosphaera ) were capable of vesicle formation. All vesicles were found to be acquired by human monocytes (Fig. 6 ), and stimulate IL-8 secretion (Fig. 7 , P > 0.05). For detailed proteomic and metabolomic studies, this study focused on vesicles from Methanobrevibacter species, the most abundant archaea in the human gut microbiome, comprising up to 4% of the microbiome 86 . Methanobrevibacter species rely on syntrophic bacterial partners that provide small organic compounds like H 2 (or formate) and CO 2 for methanogenesis 63,87,88 . The bacterial partner benefits from this interaction, as potentially inhibiting end products of fermentation are efficiently removed 63,87,88 . As such, a well-regulated and controlled interaction with bacterial syntrophic partners is highly crucial for Methanobrevibacter species. Adhesins, which were found to be highly accumulated in archaeal vesicles, have been identified to be important communication vehicles. For instance, Methanobrevibacter influences the metabolism of Christensenella minuta , shifting short-chain fatty acid (SCFA) production from butyrate to acetate 89 . This complex communication system, regulating the metabolic processes of both partners, is believed to be mediated by Methanobrevibacter surface adhesins, leading to significant physiological changes in the involved microorganisms 89 . From the bacterial kingdom, numerous adhesins are known to mediate interaction, colonization, infection and host interaction, making them key targets in bacterial pathogenesis 90,91 . Considering that adhesins are highly enriched in AEVs, as shown in Fig. 4 B-D, the importance of AEVs for archaeal-bacterial and archaeal-host interactions over longer distances becomes evident. In Methanobrevibacter ruminantium , a prevalent Methanobrevibacter species in ruminants, 5% of the genome encodes adhesins. Among them, adhesin Mru_1499 has been identified as a crucial factor allowing M. ruminantium M1 to bind and interact with hydrogen-producing protozoa and bacteria (i.e. Butyrivibrio proteoclasticus ) in the rumen, facilitating efficient methane production 62 . Other adhesins facilitate adhesion to host cells and tissues, allowing microorganisms to establish and persist within the host environment. Next to the upregulation of adhesins upon syntrophic interactions with hydrogen-producing microorganisms, adhesins were found to be increased also under nicotinic acid limitation (vitamin B3) 62,92,93 , indicating a complex interplay of metabolite-availability and the need for interaction with the microbial community and/ or the host. Enriching adhesins on mobile vehicles such as AEVs offers numerous benefits, including the ability to reach communication partners beyond the immediate physical proximity of the non-motile archaeal cells potentially enabling even a global regulation of bacterial metabolism. It must be considered that also the host is a target of the AEVs, as indicated by the efficient uptake of AEVs in human monocytes, and the profound response of epithelial cells (Figs. 6 and 7 ). It shall be mentioned that archaeal adhesins are believed to be heavily glycosylated 94 . Glycosylation is often species-specific, which could explain the different responses of HT-29 cells to AEVs from Methanobrevibacter smithii ALI and Methanobrevibacter intestini, despite similar overall AEV assembly (Fig. 2 , 3 , and 4 ). This highlights the importance of studying adhesin glycosylation patterns to understand their role in host-microbe interactions. The metabolic profiling of AEVs indicates increased levels of aspartic acid and glutamate (Fig. 5 ), which is intriguing and warrants further investigation. These findings suggest a potential link between AEVs and the gut-brain axis (as discussed in the results section), opening new avenues for research into how these vesicles might influence host physiology and neurological processes. Moreover, AEVs might possess similar capabilities to BEVs. In fact, BEVs have been shown to be able to interact with neighboring cells, cross the intestinal barrier, and enter the bloodstream, potentially reaching distant tissues, including the brain 10,95 . These traits can be exploited to use AEVs as potential next-generation drug delivery vehicles or targeted delivery systems, as has been already shown before by EVs of probiotic bacteria 96–98 . In addition, similar to BEVs, AEVs could also serve as potential postbiotics, substances comprising inactivated microbes and/or their components that confer beneficial effects on the host 99 . In summary, the identification of AEVs and their components provides significant insights into the complex interactions within the gut microbiome, highlighting the critical role of Methanobrevibacter adhesins in microbial communication and host interaction. This understanding could pave the way for novel therapeutic strategies targeting microbial interactions and their impacts on host health. Conclusion Recent investigations have expanded our understanding of EVs beyond the bacterial domain, revealing their presence and significance in other microbial realms. Notably, the human archaeome, comprising archaeal communities inhabiting various niches within the human body, has emerged as a newfound player in the EV landscape. Archaea, once predominantly studied in extreme environments, have now been recognized as integral components of the human microbiota, exerting subtle yet profound influences on human health and disease. The revelation of EV production by the human archaeome introduces a new dimension to our comprehension of microbial communication within the human body. While the specific roles and functions of archaeal EVs remain largely unexplored, their existence suggests an intricate network of interdomain interactions shaping the dynamics of the human microbiome. Furthermore, the similarities and distinctions between bacterial and archaeal EVs present intriguing avenues for comparative studies, offering insights into the evolutionary origins and adaptive strategies of extracellular vesicle-mediated communication in diverse microbial taxa. Methods Source of microorganisms. The human gut derived strains Methanobrevibacter smithii ALI (DSM 2375), and Methanosphaera stadtmanae (DSM 3091, type strain) were obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ) GmbH, Braunschweig, Germany. Candidatus M. intestini WWM1085 (DSM 116060) was obtained from the Department of Microbiology, University of Illinois, USA, where it was isolated from a stool sample of a healthy woman 24 . In the following, we will use the abbreviation “M. intestini” instead of Candidatus M. intestini. M. smithii GRAZ-2 (DSM 116045) was isolated in 2018 at the Medical University of Graz, Graz, Austria, from a stool sample of a healthy woman 24 . Instead of opting for the Methanobrevibacter smithii type strain (PS, DSM 861), our choice was M. smithii ALI, as it sourced from a human fecal sample and not from sewage water. Enterotoxigenic Escherichia coli (ETEC) H10407 and Bacteroides fragilis ATCC® 25285 have been reported previously 25 . Growth media and cultivation. For the cultivation of all methanogens standard methanogenium medium (MS) with some modifications as previously described 24 . For vesicle production, aliquots of 250 ml media in 1000 ml infusion bottles were sealed, pressurized with H 2 /CO 2 (4:1) and autoclaved. Before inoculation and incubation at 37°C, sodium acetate (0.001g/ml, anoxic, sterile) and yeast extract (0.001g/ml, anoxic, sterile, YE) were added to the media. Vesicles of ETEC and B. fragilis were retrieved from stocks prepared earlier 25 . Electron microscopy Electron microscopy (EM) was undertaken at the Core Facility Ultrastructure Analysis, Medical University of Graz, Graz, Austria and at the Core Science Resources Quadram Institute Bioscience, Norwich, United Kingdom. For ultrastructural analyses of cells, isolates were cultivated in 20 ml aliquots in 100 ml serum bottles for 7 days under anaerobic conditions at 37°C in an incubation shaker (shaking speed: 80 rpm). Followed by the centrifugation of 2 ml of medium containing each strain at 4000 g, 4°C, for 10 min. Cell pellets were then directly handed over to the Core Facility Ultrastructures, Medical University Graz, Graz, Austria for further preparation. AEVs (1x10 11 /ml) were directly handed over to the Core Science Resources Quadram Institute Bioscience, Norwich, United Kingdom. Transmission electron microscopy: thin sections and tomography Cells were fixed in 2.5% (w/v) glutaraldehyde and 2% (w/v) paraformaldehyde in 0.1 M cacodylate buffer, pH 7.4, for 1 h, postfixed in 1% (w/v) osmium tetroxide for 2 h at room temperature, dehydrated in graded series of ethanol and embedded in TAAB (Agar Scientific, Essex, GB) epoxy resin. Ultrathin sections (70 nm thick) were cut with a UC 7 Ultramicrotome (Leica Microsystems, Vienna, Austria) and stained with lead citrate for 5 min and with platinum blue for 15 min. Images were taken using a Tecnai G2 20 transmission electron microscope (Thermo Fisher) with a Gatan ultrascan 1000 charge coupled device (CCD) camera (temperature − 20°C; acquisition software Digital Micrograph; Gatan, Munich, Germany). The acceleration voltage was 120 kV. The tilt series was reconstructed using FLARA, a joint alignment and reconstruction algorithm for electron tomography. This iterative algorithm allows for acquisitions without fiducial gold markers, since an effective shift computation can be obtained by using a global alignment technique based on a linearized approximation of the disruptive shifts in each iteration26. For negative staining cell suspensions were placed on glow discharged carbon coated copper grids for 1 min. The solution was removed after incubation by filter paper stripes. A drop of 1% aqueous uranyl acetate solution was placed afterwards for 1 min, dried with filter paper and later on air dried at room temperature. Specimens were examined with an FEI Tecnai G 2 (FEI, Eindhoven, Netherlands) equipped with a Gatan ultrascan 1000 charge coupled device (CCD) camera (-20°C, acquisition software Digital Micrograph, Gatan, Munich, Germany). AEV suspensions were visualized using negative staining with TEM. Briefly, 4 µL AEV suspension was adsorbed to plasma-pretreated carbon-coated copper EM grids (EM Solutions) for 1 min before wicking off with filter paper and negatively staining with 1% Uranyl Acetate solution (BDH 10288) for 1 min. Grids were air-dried before analysis using a FEI Talos F200C electron microscope at 36,000×-92,×000 magnification with a Gatan OneView digital camera. Scanning electron microscopy For scanning electron microscopy, cells were affixed to coverslips and treated with a fixing solution consisting of 2% paraformaldehyde and 2.5% glutaraldehyde in 0.1 M phosphate buffered saline (pH 7.4). Subsequently, a graded ethanol series was used for dehydration. Post-fixation involved 1% Osmium tetroxide for 1 hour at room temperature, followed by additional dehydration in an ethanol series (ranging from 30–100% EtOH). Hexamethyldisilazane (HMDS) was applied, and coverslips were positioned on stubs using conductive double-coated carbon tape. Imaging was performed with a Sigma 500VP FE-SEM equipped with a SEM Detector (Zeiss Oberkochen) operating at an acceleration voltage of 5 kV. AEV Isolation To obtain a sufficient amount of biomass for the isolation of AEVs, 250 ml of MS medium was aliquoted into 1000 ml infusion bottles (VWR) and further handled the same way as described above. These cultures were then cultivated for 10 days under anaerobic conditions at 37°C in an incubation shaker (shaking speed: 80 rpm). When the pressure of cultivation bottles dropped due to growth, they were re-gassed with H 2 /CO 2 . Growth was surveyed by optical density photometry at 600 nm. On day ten, the cell suspensions were centrifuged at 14,000 x g, 4°C, 20 min (Thermo Scientific™ Sorvall™ LYNX™ 6000). To remove cell debris and remaining cells, the supernatant was filtered with 0.22 µm PES bottle-top filters (Fisherbrand™ Disposable PES Bottle Top Filters). If not immediately processed, the supernatant containing the vesicles was stored at 4°C. Isolation of vesicles was done according to Stentz et al. 27 (Workflow see Supplementary Fig S1). In brief, a filtration cassette (Vivaflow 50R, 100,000 MWCO, Hydrostat, model VF05H4, Sartorius or Vivaflow 200 100,00 MWCO, PES, model VF20P4) was used to concentrate 1 L of sample down to approx. 5 ml. Then, 500 ml PBS buffer (pH 7.4) was added for washing purposes, and the liquid was concentrated to 1–4 ml. The sample was then centrifuged for 20 min at 10,000 g, 4°C to remove protein and lipid aggregates. Next, the sample was transferred to Pierce™ Protein Concentrators (PES, 100,000 MWCO, Thermo Scientific) and centrifuged at 3,000 g until the samples were concentrated down to 1 ml. Residual contaminants and proteins were further eliminated through size exclusion chromatography (SEC) using an IZON qEV1 column (pore size 35 mm) according to the manufacturer’s instructions. The vesicles were eluted in the 2.8 ml fraction containing the purified extracellular vesicles underwent a final filter sterilization using a 0.22 µm syringe filter (ROTILABO® PES, 0,22 µm), and were subsequently stored at 4°C until further use. To ensure that the final AEV suspension does not contain any yeast vesicles or other residues, the YE was sterile-filtered previous to medium preparation. For the metabolomics analyses, 1 L of blank MS medium underwent the same procedure to serve as a control. BEV Isolation BEVs for the HT-29 experiment were isolated as described previously with minor modifications 25,28 . Briefly, overnight cultures were either grown with aeration (180 rpm, Infor shaker) in case of ETEC or anaerobically (GasPak™ EZ Systems, BD) in case of B. fragilis to ensure sufficient growth. The respective cultures were diluted (1:100) in BHI medium and grown at 37°C either with aeration for 8 h or overnight anaerobically (GasPak™ EZ Systems, BD). The cells were then removed from the supernatant by centrifugation (9,000 x g, 15 min) and subsequent sterile filtration (0.22 µm). The BEVs present in the supernatant were pelleted through subsequent ultracentrifugation (150,000 x g, 4°C, 4 h), resuspended in appropriate volumes of PBS to generate a BEV suspension 1000-fold more concentrated than in the original culture supernatant. Quantification and size distribution of BEVs were investigated by nanoparticle tracking analysis (NTA) using a Nanosight NS300 (see below). AEV characterization Nanoparticle tracking analysis (NTA) Quantification and size distribution of AEVs were investigated by nanoparticle tracking analysis (NTA) using ZetaView and Nanosight NS300. ZetaView was used by following established protocols 27,29 . In brief, particles were quantified using the ZetaView instrument (Particle Metrix, Germany) with ZetaView (version 8.05.12 SP1) software running a 2 cycle 11 position high frame rate analysis at 25°C. Samples were diluted with ultrapure water allowing the optimal detection range. Camera control settings: 80 Sensitivity; 30 Frame Rate; 100 Shutter. Post-acquisition parameters: 20 Min Brightness; 2000 Max Area; 5 Min Area; 30 Trace Length; 5 nm/Class; 64 Classes/Decade. For NanoSight NS300 (Malvern Instruments, UK) samples were diluted in 1x PBS according to the manufacturer’s guidelines (final concentration between 10 7 − 10 9 particles per ml), and a 405 nm laser was used. Between samples, the instrument was flushed with 10% Ethanol and Aqua.dest. Reads of 1-minute duration were performed in five replicates for each sample with the following capture settings: cell temperature: 25°C, syringe load/flow rate: 30, camera: sCMOS. For capture settings, camera level was adjusted so that all particles were distinctly visible (Camera level 12–15). The ideal detection threshold was set including as many particles as possible and debris (blue cross count) with a maximum of five (detection threshold 5). Data output was acquired using NanoSight NTA software version 3.3 (Malvern Instruments). For each sample, the mean particle number in the Experiment Summary output was adjusted by the dilution factor. Protein, DNA, and RNA content As previously described 30–34 , quantification of vesicle content, including protein, DNA, and RNA, was conducted using the Qubit® Protein Assay, Qubit® dsDNA high sensitivity assay, and RNA high sensitivity assay kits, respectively (Thermo Fisher Scientific). Protein, DNA, and RNA measurements were performed using a Qubit® 4 or Qubit® 3 Fluorometer. Instructions of the manufacturer were followed. Lipid content The quantification of lipid content in AEVs was conducted using the FM4-64 lipophilic fluorescent dye and a linoleic acid standard, a method previously employed for bacterial extracellular vesicle (BEV) lipid quantification 35 . The modified procedure for quantifying vesicles released in culture was previously described in Juodeikis et al. 29 and includes the following steps: In duplicate, 20 µL of 30 µg/ml FM4-64 (Thermo Fisher Scientific) was combined with 180 µL of filtered culture supernatant or a linoleic acid standard in water (100, 75, 50, 20, 10, 5, 1, 0 µg/ml, prepared from a 1 mg/ml stock) in black 96-well plates. Following a 10-minute incubation at 37°C, endpoint fluorescence was analyzed using the FLUOStar Omega microplate reader with pre-set FM 4–64 settings (Excitation: 515 − 15; Dichroic: auto 616.2; Emission 720 − 20), employing an enhanced dynamic range. Linear standard curves from the linoleic acid samples were established for lipid quantification. Proteomics Protein profiles of whole cell lysates (WCL) and AEVs were analyzed. Therefore, 20 mg of cell biomass (3 replicates per species) were subjected to extensive ultrasonication with 400 µl of PBS. Cell debris was removed with centrifugation at 800 g at 4°C, for 5 min. The supernatants were collected for proteomic analysis. The protein content of the whole cell lysate was determined by Pierce BCA protein assay according to the manufacturer's protocol (Thermo, USA). Protein concentration of AEVs was measured by Qubit® Protein Assay (Thermo Fisher Scientific), as described above. Mass spectrometry analysis For LC-MS/MS analysis, 2 (for AEVs) or 5 µg (for WCLs) of protein were reduced and alkylated for 10 min at 95°C with final 10 mM TCEP (tris(2-carboxyethyl)phosphine) and 40 mM CAA (2-Chloroacetamide). The sample was processed according to the SP3 protocol 36 and digested overnight with trypsin (Promega, enzyme/protein 1:50). Peptides were desalted using SBD-RPS tips as previously described 37 . 400 ng per sample (re-dissolved in 2% acetonitrile/0.1% formic acid in water) was subjected to LC-MS/MS analysis. Protein digests were separated by nano-HPLC (Dionex Ultimate 3000, Thermo Fisher Scientific(Dionex Ultimate 3000) equipped with a C18, 5 µm, 100 Å, 100 µm x 2 cm enrichment column and an Acclaim PepMap RSLC nanocolumn (C18, 2 µm, 100 Å, 500 x 0.075 mm) (all Thermo Fisher Scientific, Vienna, Austria). Samples were concentrated on the enrichment column for 5 min at a flow rate of 15 µl/min with 0.1 %formic acid as isocratic solvent. Separation was carried out on the nanocolumn at a flow rate of 300 nl/min at 60°C using the following gradient, where solvent A is 0.1 %formic acid in water and solvent B is acetonitrile containing 0.1 %formic acid: 0–5 min: 2 %B; 5-123 min: 2–35 %B; 123–124 min: 35–95 %B, 124–134 min: 95 %B; 134–135 min: 2 %B; 135–150 min: 2% B. The maXis II ETD mass spectrometer (Bruker Daltonics, Germany) was operated with the captive source in positive mode with the following settings: mass range: 200–2000 m/z, 2 Hz, capillary 1,600 V, dry gas flow 3 L/min with 150°C, nanoBooster 0.2 bar, precursor acquisition control top 20 (collision induced dissociation (CID). The mass spectrometry proteomics data were deposited to the ProteomeXchange Consortium 38 via the partner repository with the dataset identifier PXD053245 (Reviewer access details: Log in to the PRIDE website using the following details: PDX accession: PXD053245;Username: [email protected] ; Password: MFqECDz7Uyv6) 38 . The LC-MS/MS data were analyzed by MSFragger 39,40 by searching the public Methanobrevibacter protein databases (UP000232133; UP000003489; UP000004028; UP000018189; UP000001992), the archaeal protein catalogue described in Chibani et al. 22 and a list of common contaminants 41 . Additional information on proteins found in all vesicles was retrieved via MaGe 42 and the implemented functions SignalP (version 4.1) 43 , MHMM (version 2.0c) 44,45 and InterProScan 46,47 , as well as from the InterPro Database 47 (Supplementary Table 5). Carbamidomethylation of cysteine and oxidation on methionine were set as a fixed and as a variable modification, respectively. Detailed search criteria were used as follows: trypsin, max. missed cleavage sites: 2; search mode: MS/MS ion search with decoy database search included; precursor mass tolerance ± 20 ppm; product mass tolerance ± 15 ppm; acceptance parameters for identification: 1% protein FDR 48 . Data from EV and whole cell lysates were processed with Perseus software version 1.6.15.0. Data was filtered for decoy hits and contaminants. After log2 transformation, and subtracting the median from the column proteins were filtered for containing at least 2 valid values in at least one group. Mass spectrometry derived AEV metabolomics Biological triplicates of the vesicle preparations were used for the LC-MS analysis, and a technical duplicate of a non-cultured medium that had passed through the pipeline for vesicle isolation was used as a medium blank. All samples were stored at -70°C until processing at the Vienna BioCenter Metabolomics Core Facility. The samples were diluted with 50 µL ACN and subjected to analysis with liquid chromatography-mass spectrometry (LC-MS). 11 µL of each sample was pooled and used as a quality control (QC) sample. Samples were randomly injected on an iHILIC®-(P) Classic HPLC column (HILICON AB, 100 x 2.1 mm; 5 µm; 200 Å, Sweden) with a flow rate of 100 µL/min delivered through an Ultimate 3000 HPLC system (Thermo Fisher Scientific, Germany). The stepwise gradient has a total run time of 35 min, starts at 90% A (ACN), and takes 21 min to 60% B (25 mM ammonium bicarbonate) followed by 5 min hold at 80% B and a subsequent equilibration phase at 90%. The LC was coupled to a high-resolution tandem MS instrument (Q-Exactive Focus, Thermo Fisher Scientific, Germany). The ionization potential was set to + 3.5/-3.0 kV, the sheet gas flow to 20, and an auxiliary gas flow of 5 was used. Samples were flanked by a blank and a QC sample for background labeling and data normalization, respectively. The obtained data set was processed by “Compound Discoverer 3.3 SP2” (Thermo Fisher Scientific). Annotation of the compounds was done through searching against our internal mass list database generated with authentic standard solutions (highest confidence level). Additionally, the mzCloud database was searched for fragment matching and ChemSpider hits were obtained using BioCyc, Human Metabolome Database, E. coli Metabolome Database, and KEGG databases. Only metabolites identified with highest confirmation (match with internal database) were examined in more detail; additional ones are provided in Supplementary Table 7). The log2 fold changes, as well as p-values, were calculated by the Compound Discoverer software (Tukey HSD test (posthoc), after an analysis of variance (ANOVA) test). Co-incubation experiments with cell lines Cytotoxicity tests of AEVs and BEVs 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) cell viability assays were routinely performed at the end of the HT-29 cell culture assays 49 , but no significant reduction in metabolic activity could be observed for any condition used in this study (data not shown). Additionally, CellTiter-Glo® 2.0 Cell Viability Assay (Promega) was used to investigate the cytotoxicity of AEVs on THP1-Blue cells, but no reduction in the viable cells could be detected (data not shown). Confocal Microscopy M. smithii ALI, M. intestini, M. smithii GRAZ-2, and M. stadtmanae -derived AEVs (1x10 11 /ml) were labeled with 5% DiO at 37°C for 30 minutes. Labeled DiO - AEVs (1x10 11 /well [10 µl]) were added to THP1-b cell monolayers cultured on collagen solution (Merck) coated 12-well chamber slides (IBIDI) overnight (16 hrs). THP1-b monocytes were previously induced to differentiate into macrophages using 150 nM PMA (Phorbol 12-myristate 13-acetate; Sigma, P8139). Samples were fixed using Pierce 4% PFA (ThermoFisher), permeabilized with 0.25% Triton X1000 (Sigma), and blocked with 10% goat serum in PBS. For nuclear visualization, cells were incubated with Hoechst 33342 (ThermoFisher), Alexa 647-Phalloidin to visualize intracellular membranes. As a second approach, AEVs were incubated with Archaea specific primary antibodies (Davids Biotechnologie GmbH, affinity purified, specific for Methanobrevibacter and Methanosphaera ) and AF647 as the secondary antibody, and cells were labeled with Hoechst 33342 (ThermoFisher). Images were taken using a Zeiss LSM880 confocal microscope equipped with a 63x/1.40 oil objective. Fluorescence was recorded at 405 (blue, nucleus), 488 (green, AEVs), and 594 nm (red, intracellular membranes or AEVs). The red channel was adjusted using the ZEISS ZEN 3.9 (ZEN lite) software by the best-fit function. HT-29 cytokine release The HT-29 cytokine release assay was performed at the Institute of Molecular Biosciences, University of Graz. HT-29 (intestinal epithelial cells) were grown in T-175 tissue culture flask, containing Dulbecco's Modified Eagle's medium/ Nutrient F-12 (DMEM-F12) medium (Gibco, USA) supplemented with 10% fetal bovine serum (FBS), Penicillin-Streptomycin (100 µg/ml streptomycin and 100 Units/ml penicillin) and L-Glutamine (2 mM) at 37 o C in a CO 2 incubator. To investigate the pro-inflammatory potency of AEVs and BEVs, HT-29 cells were seeded in a 24 well tissue culture plates at a concentration of 6 x 10 5 cells/well and cultivated for 24 h in DMEM-F12 medium supplemented with 10% fetal bovine serum (FBS), Penicillin-Streptomycin and L-Glutamine. Then, intestinal epithelial cells were washed once with PBS and the medium was replaced with AEVs or BEVs (10 8 particles/ ml) resuspended in DMEM-F12 medium without FBS. After incubation for 20 h the cell culture supernatant was harvested, centrifuged for 2500 rpm at 4°C for 10 min to remove the cell debris and stored at -20°C for subsequent Interleukin 8 (IL-8) quantification by ELISA, which was performed as previously described according to the manufacturer’s protocol 25 . Statistics and data visualization Vesicle properties (Concentration, size, nucleic acids, and protein content) and metabolites were plotted as boxplots in R (R-Core-Team, 2024) using the ggplot2 Package (v3.5.1) 50 . Creation of Venn diagrams was performed by using the online tool interactiVenn 51 . PCA was created with Perseus software (v1.6.15.0) 52 . The overview of proteins identified in archaeal vesicles and whole cell lysates, as well as proteins annotated as adhesins, were displayed in heatmaps using ggplot2 (v3.5.1) 50 , with data transformation performed using the reshape2 53 package (v1.4.4; Wickham, 2007). Barchart of mean intensities of protein categories was plotted with ggplot2 (v3.5.1) 50 , and dplyr (v1.1.4) 54 was used for the calculation of mean and standard deviation. IL-8 excretion in the HT-29 cell line was visualized as a bar chart using ggplot2 (v3.5.1) 50 , with data transformation by reshape2 53 (v1.4.4; Wickham, 2007), FSA (v0.9.5) 55 , and ggsignif (v0.6.4) 56 . For IL-8 excretion Kruskal-Wallis test followed by Dunn’s Multiple comparison where all EV samples were compared to the NTC (no treatment control). Declarations Competing interests None declared. Funding This research was funded in whole or in part by the Austrian Science Fund (FWF) [ 10.55776/F83 , 10.55776/P32697 , and 10.55776/COE7 ]. The authors acknowledge the support of the ZMF Galaxy Team: Core Facility Computational Bioanalytics, Medical University of Graz, funded by the Austrian Federal Ministry of Education, Science and Research, Hochschulraum-Strukturmittel 2016 grant as part of BioTechMed Graz. The Vienna BioCenter Core Facilities (VBCF) Metabolomics Facility acknowledges funding from the Austrian Federal Ministry of Education, Science & Research; and the City of Vienna. Author contributions The study was designed by CME and VW. VW, PM, and TZ isolated the vesicles, together with help from RS, EJ, and SRC. Vesicle biophysical characterization was done by VW. VW and BD performed proteomics and analyzed the data with the supervision of HK and CME. Metabolomics was performed by TKoe and GG, and data were analyzed by VW and CME. Electron microscopy was performed by DP, KH, DK, and KG. HT and SS performed experiments with HT-29 cells. Experiments with macrophages were performed by VW, with the help of RS and EJ. The lipid assay was performed by RJ. VW and CME wrote the manuscript, and TS, CK, RM, TKue, and TW contributed to the writing of the manuscript and figure preparation. The manuscript was read and approved by all authors. Acknowledgements We thank Stefanie Duller for providing electron micrographs. The support for V. Weinberger through the local dissertation program MolMed is acknowledged. We acknowledge the JIC Bioimaging facility and staff for their contribution to this publication. Data availability All original data are either provided in the supplementary information/ tables, and/or on our Github repository ( https://github.com/vikwein/Archaeal_extracellular_vesicles ). References Gill S, Catchpole R, Forterre P (2019) Extracellular membrane vesicles in the three domains of life and beyond. FEMS Microbiol Rev 43 Brown L, Wolf JM, Prados-Rosales R, Casadevall A (2015) Through the wall: Extracellular vesicles in Gram-positive bacteria, mycobacteria and fungi. Nature Reviews Microbiology vol. 13 Preprint at https://doi.org/10.1038/nrmicro3480 Briaud P, Carroll RK (2020) Extracellular vesicle biogenesis and functions in gram-positive bacteria. 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Supplementary Files SupplementaryVesiclepaper.pdf Supplementary Information - figures datacollectionvesiclepaper.xlsx Supplementary Information - tables Cite Share Download PDF Status: Published Journal Publication published 03 Jun, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4687775","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":327241764,"identity":"e0cf252c-fd92-451f-9832-ac70144945dd","order_by":0,"name":"Christine 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Graz","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Schild","suffix":""}],"badges":[],"createdAt":"2024-07-04 16:20:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4687775/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4687775/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-60271-w","type":"published","date":"2025-06-03T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60491166,"identity":"ea8bf387-b6e4-49a4-92e8-28afb1c2cd2e","added_by":"auto","created_at":"2024-07-17 10:43:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":978517,"visible":true,"origin":"","legend":"\u003cp\u003eUltrastructure of cells and vesicles. Panels A, E, H, K: Scanning electron micrographs of whole cells. B, F, I, J: Transmission electron micrographs of whole cells showing vesicles inside or attached to the cells. C, D, G, L: isolated vesicles, transmission electron micrographs. The arrows indicate the presence of AEVs.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/d05e891af64771b21114b054.png"},{"id":60492458,"identity":"9eb83add-1d7c-4523-92f0-774045149803","added_by":"auto","created_at":"2024-07-17 10:59:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":148908,"visible":true,"origin":"","legend":"\u003cp\u003eVesicle properties of \u003cem\u003eM. smithii\u003c/em\u003e ALI, M. intestini, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, and \u003cem\u003eM. stadtmanae\u003c/em\u003e. (A) Concentration [particles/ml], (B) Size [nm]. (C) Protein, (D) DNA, and (E) RNA content was normalized to [µg/10\u003csup\u003e10\u003c/sup\u003e particles].\u0026nbsp; One outlier was removed in (D), and (E).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/8876826bace6f8661816ca6d.png"},{"id":60491760,"identity":"8e2533dc-2c18-4837-9f36-2e3c56b6237f","added_by":"auto","created_at":"2024-07-17 10:51:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":233803,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams constructed with proteins based on a prevalence in 3 of 3 replicates per group of WCL_ALI, WCL_int, EV_ALI or EV_int. (A) WCL_ALI vs. WCL_int, (B) EV_ALI vs. EV_int, (C) WCL_ALI vs. EV_ALI vs. EV_int vs. WCL_int, (D) WCL_ALI vs. EV_ALI, and (E) WCL_int vs. EV_int. EV_ALI, vesicles M. smithii ALI; EV_int, vesicles M. intestini; WCL_ALI, whole cell lysate \u003cem\u003eM. smithii \u003c/em\u003eALI; WCL_int, whole cell lysate M. intestini.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/dc07a0a1bc8a59f018a26e87.png"},{"id":60491762,"identity":"39c1da94-c35a-4c45-b6e9-8ff50ffbf4fa","added_by":"auto","created_at":"2024-07-17 10:51:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":427312,"visible":true,"origin":"","legend":"\u003cp\u003e(A) PCA plot, proteins prevalent in 3 of 3 replicates per group.\u0026nbsp; EV_ALI, vesicles \u003cem\u003eM. smithii\u003c/em\u003e ALI; EV_int, vesicles M. intestini; WCL_ALI, whole cell lysate\u003cem\u003e M. smithii\u003c/em\u003e ALI; WCL_int, whole cell lysate M. intestini. (B) 229 overlapping proteins found in the proteomes of \u003cem\u003eM. smithii\u003c/em\u003e ALI (left, n=3 biological replicates) and M. intestini (right, n=3 biological replicates) vesicles, grouped by their intensities (reflected by the size of the circles) and (putative) functions (details can be retrieved from Supplementary Table CME-2). Visualization was done via RawGraphs\u003csup\u003e60 \u003c/sup\u003eand InkScape\u003csup\u003e61\u003c/sup\u003e (C) Barchart showing the mean intensities of protein categories in vesicles (EV) and whole cell lysates (WCL). Only proteins which were found in 3+3 biological replicates of \u003cem\u003eM. smithii \u003c/em\u003eALI (ALI) and M. intestini (int) (n=229) are included (Data: Supplementary Table 4). (D) Heatmap depicts the presence of 46 proteins annotated as adhesin/adhesion/IG-like present in six out of six AEV extracts (EV_ALI, EV_int) compared to the whole cell lysate (WCL_ALI, WCL_int). EV_ALI, vesicles \u003cem\u003eM. smithii\u003c/em\u003e ALI; EV_int, vesicles M. intestini; WCL_ALI, whole cell lysate \u003cem\u003eM. smithii\u003c/em\u003e ALI; WCL_int, whole cell lysate M. intestini.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/6b94200d2a9acdd370bbed1b.png"},{"id":60491758,"identity":"17d84e39-4e5c-474e-8d17-4ac1613bf662","added_by":"auto","created_at":"2024-07-17 10:51:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":92237,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolomics: Metabolites detected in archaeal vesicles (biological triplicates), compared to the culture medium control (technical duplicates). The Y-axis shows the normalized peak area (LC-MS). Significantly changed compounds are highlighted by an asterisk. The line inside the box represents the median of the data for each category; the box spans first to third quartile. Whiskers display the smallest and largest values.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/10434d6d2d5274533644803a.png"},{"id":60492459,"identity":"18a21e97-bebc-475c-a146-ae398b1b0f0a","added_by":"auto","created_at":"2024-07-17 10:59:46","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1562950,"visible":true,"origin":"","legend":"\u003cp\u003eImmunofluorescence microscopy of DiO-labeled AEVs (green) acquired by human macrophages (24h incubation). Macrophage monolayers were stained with antibodies to visualize cytoskeleton (Alexa 647-Phalloidin, red), nuclei (Hoechst 33342, blue). Macrophage incubation with (A) \u003cem\u003eM. smithii\u003c/em\u003e ALI derived EVs, (B) M. intestini derived EVs, (C) \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2 derived AEVs, (D) \u003cem\u003eM. stadtmanae\u003c/em\u003ederived AEVs. (E) Representative z-stack of \u003cem\u003eM. stadtmanae\u003c/em\u003e deriver AEVs acquired by a macrophage.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/99dbb8b6172c6cfd98fd3bfa.png"},{"id":60491172,"identity":"ef6ce3ed-f4f0-4a37-857d-d4c1c116c98f","added_by":"auto","created_at":"2024-07-17 10:43:46","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":113801,"visible":true,"origin":"","legend":"\u003cp\u003eIL-8 response in HT-29 intestinal cells to AEVs and BEVs. Cytokine levels were quantified by ELISA in supernatants of HT-29 intestinal cells incubated for 16 h with equal particle amounts of AEVs or BEVs. Donor strains of the AEVs or BEVs are indicated on the X-axis. Incubation with PBS served as no treatment control (NTC). Data are indicated as the median ± interquartile range (\u003cem\u003en\u003c/em\u003e = 6). Asterisks highlight significant differences to the NTC (*, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001 by Kruskal-Wallis test, followed by Dunn’s \u003cem\u003epost hoc\u003c/em\u003e test). Bar heights represent the median of the data for each category; error bars represent the range from the first to the third quartile.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/a1ba961a9a3f1c3ddfc2fca4.png"},{"id":83887724,"identity":"d8a464e2-83a7-49a6-9074-f7b73cfa076b","added_by":"auto","created_at":"2025-06-04 07:09:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4642424,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/735c64b4-d942-4fc1-b022-ca9176183060.pdf"},{"id":60491169,"identity":"b425b6b9-3cdf-48e5-ae73-f8ab890e7216","added_by":"auto","created_at":"2024-07-17 10:43:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":760429,"visible":true,"origin":"","legend":"Supplementary Information - figures","description":"","filename":"SupplementaryVesiclepaper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/ff2481f70b13bb62c9bf129d.pdf"},{"id":60491173,"identity":"e16e50a2-eea9-4045-b3ce-e1049e5ae9e2","added_by":"auto","created_at":"2024-07-17 10:43:46","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":560476,"visible":true,"origin":"","legend":"Supplementary Information - tables","description":"","filename":"datacollectionvesiclepaper.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4687775/v1/137603eb30baca75bf2f10f4.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Proteomic and Metabolomic Profiling of Archaeal Extracellular Vesicles from the Human Gut","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAll organisms have evolved various signaling mechanisms to convey crucial biological information across cells, tissues, and organs\u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. Among these mechanisms are extracellular vesicles (EVs), which are small membrane-bound spherical particles produced and released by cells of all three domains of life\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the gastrointestinal tract (GIT), extracellular vesicles produced by commensal bacteria (bacterial extracellular vesicles, BEVs) mediate intra- and inter-kingdom interactions, maintaining the microbiome ecosystem and promoting interactions with the host \u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBEVs have garnered considerable attention in recent years due to their diverse roles in intercellular communication, pathogenesis, stress tolerance, immune stimulation, and host-microbe interactions\u003csup\u003e3\u0026ndash;7\u003c/sup\u003e. These small, membrane-bound structures serve as vehicles for the transport of biomolecules such as proteins, nucleic acids, metabolites and lipids between bacterial cells, as well as between bacteria and their host environments \u003csup\u003e4,8\u0026ndash;12\u003c/sup\u003e. Understanding the mechanisms underlying BEV biogenesis, cargo loading, and their impact on microbial communities and host physiology is critical in microbiology and biomedical research \u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBEVs are divided into different categories based on either their producing bacteria (BEVs from Gram-negative and Gram-positive bacteria) or their origin and the pathway by which they are formed (outer membrane vesicles, outer-inner membrane vesicles, explosive membrane vesicles or cytoplasmic membrane vesicles)\u003csup\u003e13,14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOuter membrane vesicles (OMVs) are considered as the archetypal bacterial membrane vesicles. These OMVs usually arise from a protrusion of the outer membrane and their envelope, therefore resembling the envelope of the donor cell. They usually contain surface-associated factors, outer membrane proteins, and periplasmic content\u003csup\u003e13,14\u003c/sup\u003e. Explosive membrane vesicles on the other hand diversify BEV composition, explaining the presence of nucleic acids and cytosolic content in vesicle samples from Gram-negative bacteria.\u003c/p\u003e \u003cp\u003eIn the course of the last decade, it has become evident that BEVs of GIT-colonizing bacteria potentially influence essential functions of the intestine, and of systemic organs after their migration to the bloodstream, thereby contributing to host health\u003csup\u003e15\u003c/sup\u003e. For instance, BEVs contribute to host digestion by distributing hydrolase activities across the lumen, and can potentially influence the central nervous system following migration through the gut-brain axis\u003csup\u003e16\u003c/sup\u003e. Additionally, BEVs can act as efficient delivery vehicles of bioactive compounds, such as toxins or modulators of host cell physiology\u003csup\u003e13,14\u003c/sup\u003e. BEVs are recognized and efficiently internalized by various host cells resulting in intestinal barrier changes, immunomodulation and (patho-)physiological changes\u003csup\u003e13,14\u003c/sup\u003e. BEVs can also act on the surrounding microbiota, promoting bacterial colonization and growth as well as protecting bacteria from antibiotics and host defense peptides \u003csup\u003e11,17,18\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTriggers for vesicle formation are manifold, including factors such as media composition, growth phase, temperature, iron and oxygen availability, as well as exposure to antibiotics and stress\u003csup\u003e13,14\u003c/sup\u003e. As a consequence of the diverse triggers and various origins, the vesicle preparations likely reflect a mixture of different BEV types, which could explain variable BEV functions and effects, and experiments are sometimes non-conclusive\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRepresentatives of all three domains of eukaryotes, bacteria, and archaea, are capable of forming extracellular vesicles\u003csup\u003e19\u003c/sup\u003e. The reports on archaeal vesicles are overall fairly rare and are restricted to extremophilic archaea, namely Thermococcales and Sulfolobales. It appears that in \u003cem\u003eSulfolobus\u003c/em\u003e, for example, vesicle formation is evolutionarily related to eukaryotic ESCRT complex proteins used for the building of endosomes; however, other archaea, such as \u003cem\u003eThermococcus\u003c/em\u003e form vesicles but do lack the ESCRT complex, indicating a higher variety in vesicle formation mechanisms\u003csup\u003e19\u003c/sup\u003e. In general, a defensive function through these vesicles was proposed, but research is still ongoing\u003csup\u003e20\u003c/sup\u003e. However, archaea not only thrive in environmental ecosystems, but are also considered as reliable and prevalent constituents of the human GIT microbiome. With 1.2% relative abundance on average, \u003cem\u003eMethanobrevibacter\u003c/em\u003e and \u003cem\u003eMethanosphaera\u003c/em\u003e species are highly prevalent across individuals (\u0026gt;\u0026thinsp;90%)\u003csup\u003e21,22\u003c/sup\u003e. Trough maintaining numerous syntrophic relationships with intestinal bacteria, these archaea have the capacity to orchestrate the entire microbiome, leading to an optimized fibre degradation\u003csup\u003e23\u003c/sup\u003e. They also influence the host with respect to the provision of short chain fatty acids or mediate the reduction of gut motility, leading to constipation\u003csup\u003e18\u003c/sup\u003e. However, the mechanisms by which they interact with other microorganisms and their mode of signaling have remained unknown.\u003c/p\u003e \u003cp\u003eIn this manuscript, we focus on the recent discovery of archaeal extracellular vesicles (AEVs) produced by human archaeal representatives and present novel findings on their ultrastructure, proteome, and metabolome, as well as their interaction with human cell lines. We will discuss the implications of this discovery for our understanding of microbiome-host interactions and outline future directions for research. By integrating insights from bacterial and archaeal EV biology, we strive to unravel the complexities of microbial communication networks within the human body and their implications for health and disease.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eVesicles produced by Methanobrevibacter intestini, \u003cem\u003eM. smithii\u003c/em\u003e ALI, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2 and \u003cem\u003eMethanosphaera stadtmanae\u003c/em\u003e were visualized by electron microscopy in supernatants of cultures in the late exponential/stationary phase. Using protocols developed and optimized for BEV analysis, AEV biomass production and an isolation protocol were established to enable characterization with respect to size, composition, ultrastructure, proteome, metabolome, and interaction with mammalian cells.\u003c/p\u003e \u003cp\u003eAEV formation in all methanogen species\u003c/p\u003e \u003cp\u003eNegative staining- and ultra-thin electron-microscopy- based methods revealed the presence of vesicle-like structures within (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF,I, J) and attached to the cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, E, H, K) and in their close vicinity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) in all methanoarchaeal cultures. These were usually round shaped, approximately 87\u0026ndash;198 nm in size (~\u0026thinsp;130 nm on average, sizes measured during NTA, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D, G, L), and showed a clear, sharp edge. No vesicles were observed in culture media controls that also underwent microscopy imaging.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBiophysical AEV characteristics\u003c/p\u003e \u003cp\u003eAEVs from the methanogens \u003cem\u003eM. smithii\u003c/em\u003e ALI, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, M. intestini and \u003cem\u003eM. stadtmanae\u003c/em\u003e were purified using a centrifugation, filtration and concentration pipeline, previously established for bacterial EVs\u003csup\u003e27\u003c/sup\u003e with minor adaptations (see materials and methods). To the former described BEV isolation protocol, a centrifugation step (10.000 x g, 20 min) was added to remove residues from the culture media. The basic characteristics of the AEVs (size, concentration, nucleic acid, protein and lipid content) are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe size of the AEVs ranged from 86.9 to 197.3 nm (~\u0026thinsp;130 nm on average). M. intestini derived AEVs were found to be the largest (~\u0026thinsp;136 nm on average), and \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2-derived vesicles the smallest (~\u0026thinsp;117 nm), which were similar in size to those of \u003cem\u003eM. smithii\u003c/em\u003e ALI (~\u0026thinsp;124 nm). Overall the size of the vesicles was in the range of BEVs (20\u0026ndash;400 nm)\u003csup\u003e3,57,58\u003c/sup\u003e e.g. from enterotoxigenic \u003cem\u003eEscherichia coli\u003c/em\u003e (ETEC, ~\u0026thinsp;120 nm), but slightly smaller than BEVs e.g. from \u003cem\u003eBacteroides thetaiotaomicron\u003c/em\u003e (~\u0026thinsp;180 nm)\u003csup\u003e59\u003c/sup\u003e, and \u003cem\u003eB. fragilis\u003c/em\u003e (~\u0026thinsp;194 nm).\u003c/p\u003e \u003cp\u003eAverage concentration of the retrieved AEVs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was much lower than concentrations usually measured for BEVs, such as ETEC (6.38E\u0026thinsp;+\u0026thinsp;11 particles/ml), and \u003cem\u003eB. fragilis\u003c/em\u003e (8E\u0026thinsp;+\u0026thinsp;11 particles/ml). The concentrations were reasonably consistent for all \u003cem\u003eM. smithii\u003c/em\u003e strains, with lower concentration retrieved for M. intestini and \u003cem\u003eM. stadtmanae\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, the protein content ranged from 0.09 to 180.6 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles. On average, AEV extracts of \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2 contained the highest protein concentration (~\u0026thinsp;52 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles), whereas the lowest concentrations were found in \u003cem\u003eM. smithii\u003c/em\u003e ALI (~\u0026thinsp;7.8 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles). Regarding the lipid content, all AEVs extracts were in the range of the standard linoleic acid (20\u0026ndash;100 \u0026micro;g/ml). AEVs from M. intestini showed the highest (~\u0026thinsp;81.20 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles) and the lowest amount of lipids (~\u0026thinsp;4.9 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles on average). It has to be mentioned that the lipid content could only be detected in a few samples, as not all measurements of concentrations were found in the standard range. Overall, the DNA content of AEV extracts ranged from 0.004 to 18.27 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles. AEVs of M. intestini had the highest DNA concentration (3.14 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles), while \u003cem\u003eM. stadtmanae\u003c/em\u003e had the lowest one (0.55 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles) on average. RNA content of AEVs could not be detected in all samples, due to low concentrations. AEVs from \u003cem\u003eMethanobrevibacter\u003c/em\u003e strains contain similarly low amounts of RNA (0.08\u0026thinsp;\u0026minus;\u0026thinsp;0.014\u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles), while 0.17 \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles could be detected for \u003cem\u003eM. stadtmanae\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of archaeal vesicles\u0026rsquo; properties, namely size, concentration, protein, DNA, RNA, and lipid content. Protein, DNA, RNA, and lipid contents were normalized to \u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSize [nm]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConcentration [particles/ml]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003cp\u003e[\u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDNA [\u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRNA [\u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLipid [\u0026micro;g/10\u003csup\u003e10\u003c/sup\u003e particles]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM. smithii\u003c/em\u003e ALI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003eMin.\u003c/p\u003e \u003cp\u003eMax.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.61\u003c/p\u003e \u003cp\u003e86.90\u003c/p\u003e \u003cp\u003e148.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.16E\u0026thinsp;+\u0026thinsp;11\u003c/p\u003e \u003cp\u003e1.21E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003cp\u003e2.33E\u0026thinsp;+\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.76\u003c/p\u003e \u003cp\u003e0.26\u003c/p\u003e \u003cp\u003e16.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003cp\u003e0.04\u003c/p\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.87\u003c/p\u003e \u003cp\u003e1.75\u003c/p\u003e \u003cp\u003e10.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. intestini\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003eMin.\u003c/p\u003e \u003cp\u003eMax.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136.85\u003c/p\u003e \u003cp\u003e87.90\u003c/p\u003e \u003cp\u003e197.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003cp\u003e2.60E\u0026thinsp;+\u0026thinsp;09\u003c/p\u003e \u003cp\u003e9.20E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.89\u003c/p\u003e \u003cp\u003e7.01\u003c/p\u003e \u003cp\u003e41.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003cp\u003e0.46\u003c/p\u003e \u003cp\u003e18.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e0.07\u003c/p\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81.20\u003c/p\u003e \u003cp\u003e81.20\u003c/p\u003e \u003cp\u003e81.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003eMin.\u003c/p\u003e \u003cp\u003eMax.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117.28\u003c/p\u003e \u003cp\u003e91.30\u003c/p\u003e \u003cp\u003e138.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.69E\u0026thinsp;+\u0026thinsp;11\u003c/p\u003e \u003cp\u003e1.20E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003cp\u003e5.63E\u0026thinsp;+\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.78\u003c/p\u003e \u003cp\u003e0.09\u003c/p\u003e \u003cp\u003e180.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003cp\u003e0.001\u003c/p\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003cp\u003e11.00\u003c/p\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM. stadtmanae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003eMin.\u003c/p\u003e \u003cp\u003eMax.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.92\u003c/p\u003e \u003cp\u003e94\u003c/p\u003e \u003cp\u003e168.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.44E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003cp\u003e4.20E\u0026thinsp;+\u0026thinsp;09\u003c/p\u003e \u003cp\u003e4.08E\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003cp\u003e5.93\u003c/p\u003e \u003cp\u003e37.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003cp\u003e0.01\u003c/p\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003cp\u003e0.17\u003c/p\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.30\u003c/p\u003e \u003cp\u003e35.30\u003c/p\u003e \u003cp\u003e35.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMethanobrevibacter AEVs have comparable proteomes and show a massive enrichment in adhesins\u003c/p\u003e \u003cp\u003eThe protein cargo of \u003cem\u003eM. smithii\u003c/em\u003e ALI and M. intestini EVs were compared with that of their respective whole microbial cell proteomes (whole cell lysate, WCL). Profiling was carried out through LC-MS/MS, employing isolated AEVs and whole cell lysates (n\u0026thinsp;=\u0026thinsp;3) of \u003cem\u003eM. smithii\u003c/em\u003e ALI and M. intestini (refer to material and methods section for details). A total of 1475 vesicular proteins across all isolated EVs were identified (\u003cem\u003eM. smithii\u003c/em\u003e ALI: 801; M. intestini: 674), complemented by the identification of 2537 proteins from the whole cell lysates (WCL; \u003cem\u003eM. smithii\u003c/em\u003e ALI: 1262; M. intestini: 1275, Supplementary Fig. S3, Supplementary Table\u0026nbsp;1). Proteins were considered to be present in a sample, based on a prevalence in three out of three replicates for each group of sample (WCL \u003cem\u003eM. smithii\u003c/em\u003e ALI (WCL_ALI): 1026; WCL M. intestini (WCL_int): 1100; EVs M. smithii ALI (EV_ALI): 364, and EVs M. intestini (EV_int): 259; Supplementary Fig. S2, Supplementary Table\u0026nbsp;1). Compared to the 2047 proteins identified in BEVs derived from \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e\u003csup\u003e59\u003c/sup\u003e, the total number of proteins in methanoarchaeal EVs was much lower.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAEVs derived from \u003cem\u003eM. smithii\u003c/em\u003e ALI (EV_ALI) and M. intestini (EV_int) share 229 proteins, while having 135 and 30 unique proteins in these strains, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Only a small number of proteins (EV_ALI: 35, EV_int: 56) were detected in the vesicles but not in the whole cell lysates (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD and E). Proteins of whole cell lysates were highly similar, as 816 proteins were identified in both WCL_ALI and WCL_int (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). 173 proteins were found in all four groups (EV and WCL of both strains, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eThe PCA plot depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA illustrates different distribution patterns between whole-cell lysates (WCL) and extracellular vesicles (EVs) for both strains. Notably, it also highlights the similarities observed between WCL_ALI and WCL_int, as well as between EV_ALI and EV_int.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe protein content of the vesicles of both \u003cem\u003eMethanobrevibacter\u003c/em\u003e species was strikingly similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary Fig. S2 and S3), with 229 proteins found in all six extracts. The most abundant proteins were Adhesins/ adhesin-like proteins/ proteins with an IG-like domain, as identified through InterPro prediction (ALPs, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and C; for details on functional annotation see Materials and Methods and Supplementary Table\u0026nbsp;6); these proteins were also highly enriched compared to the whole-cell lysates (WCL, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and C; Supplementary Table\u0026nbsp;4)\u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eALPs are rarely studied in archaea, but were found to be very abundant in e.g. rumen methanogens where they account for up to 5% of all genes. It has been suggested that the ALPs serve to attach to their protozoan hosts or to the cell surface of bacteria\u003csup\u003e62\u003c/sup\u003e. ALPs have also been found in human-associated \u003cem\u003eMethanobrevibacter\u003c/em\u003e species\u003csup\u003e63\u003c/sup\u003e, for which adhesion and sugar-binding function has been proposed. Indeed, the identified vesicle-associated ALPs carried a variety of protein domains, indicative of an adhesive (Invasin/intimin cell-adhesion fragments; IG-like_fold superfamily) and polysaccharide binding functions (PbH1; pectin_lyase_fold, Pectin_lyase_fold/virulence; details for all genes and their identified domains are given in Supplementary Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eBacterial proteins containing IG-like domains exhibit a broad spectrum of functions, such as cell host adhesion and invasion. IG-like domains are also found in periplasmic chaperones and proteins that assemble fimbriae, in oxidoreductases and hydrolytic enzymes, ATP-binding cassette transporters, sugar-binding and metal-resistant proteins\u003csup\u003e64\u003c/sup\u003e. These proteins are structural components of bacterial pilus and nonpilus fimbrial systems and members of the intimin/invasin family of outer membrane adhesins, indicating their relevance for adhesion and interaction with the biological surroundings. Microbial pectin and pectate lyases are involved in the degradation of pectic components of the plant cell, which is an important trait for plant pathogens, as well as the degradation of dietary components in the gastrointestinal tract. However, this specific β-helix topology has various functions e.g. as galacturonases, or for the adhesion to mammalian cells\u003csup\u003e65\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWithin a group of transport-associated proteins, we found substantial enrichment of a protein (representative: GUT_GENOME043902_01504) with an OPT (oligopeptide transporter) superfamily domain, which in prokaryotes may contribute to iron-siderophore uptake\u003csup\u003e66\u003c/sup\u003e, indicating a potential role in iron binding.\u003c/p\u003e \u003cp\u003eA further substantial increase was observed for a putative DUF11 domain-containing protein\u003csup\u003e67\u003c/sup\u003e, which might be important for stabilizing surface wall structures in \u003cem\u003eMethanothermobacter\u003c/em\u003e sp. strain CaT2 \u003csup\u003e67\u003c/sup\u003e. Another interesting finding was the increased presence of a putative peptidase_C1, which also showed adhesin-like domains (Supplementary Tables\u0026nbsp;4 and 6).\u003c/p\u003e \u003cp\u003eMetabolite cargo of AEVs could have an effect on gut-brain-axis\u003c/p\u003e \u003cp\u003eSimilar to the proteomic analyses, the metabolic profiles of AEVs of \u003cem\u003eM. smithii\u003c/em\u003e ALI and M. intestini were overall similar, but with high variability across biological replicates, probably due to variations in input concentrations (see group CV % in Supplementary Table\u0026nbsp;7; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Strikingly, the AEVs of M. intestini revealed a significantly increased content of glutamic and aspartic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01, respectively; Supplementary Table\u0026nbsp;7; this table also includes details on statistics). Also, the AEVs of \u003cem\u003eM. smithii\u003c/em\u003e ALI revealed a substantial Log2 Fold Change (FC) compared to background samples, indicating that these amino acids are important cargos for both species. \u003cem\u003eM. smithii\u003c/em\u003e ALI were substantially loaded with arginine.\u003c/p\u003e \u003cp\u003eNotably, glutamate has been identified as a component of bacterial EVs (\u003cem\u003eB. fragilis)\u003c/em\u003e\u003csup\u003e68\u003c/sup\u003e. Besides their roles in central metabolism, both amino acids are considered to act as neurotransmitters\u003csup\u003e69\u003c/sup\u003e. Glutamate plays a fundamental role as an excitatory neurotransmitter in the central nervous and the enteric nervous system and acts, together with other metabolites, along the \u0026ldquo;microbiota-gut-brain axis\u0026rdquo;\u003csup\u003e70\u003c/sup\u003e as an \u0026ldquo;interkingdom communication system\u0026rdquo;. It is considered that the glutamatergic receptors, along the microbiota-gut-brain axis, could have an impact on multiple physiological responses in the brain and gut. As glutamate usually does not enter the bloodstream from the large intestine, AEVs could be supporting the transmission to glutamatergic enteric neurons/ receptors\u003csup\u003e70\u003c/sup\u003e. Despite its potential function as a neurotransmitter, aspartate also supports the proliferation of mammalian cells (e.g. cancer cells)\u003csup\u003e59\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCholine glycerophosphate (glycerophosphorylcholine, alpha GPC) was found to be elevated in AEVs of both species (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Also, for this compound, a potential neurological effect was described, which has been considered for the treatment of Alzheimer\u0026rsquo;s disease\u003csup\u003e71\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe origin of the salicylic acid, which was found to be increased in AEVs of both species, is unclear (potentially from chorismate), but its potential effects on the host and microbiome could include bactericidal and antiseptic action in higher concentrations\u003csup\u003e72\u003c/sup\u003e. Another compound found to be increased was oxalic acid, the latter having the characteristics of a chelating agent for metal cations, making insoluble iron compounds into a soluble complex ion, which could be an interesting trait for gastrointestinal microbiota\u003csup\u003e73\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHuman monocytes acquire AEVs\u003c/p\u003e \u003cp\u003eHuman leukemia monocytic THP-1 cells are a common model for studying monocyte/macrophage functions, signaling pathways, mechanisms, and drug and nutrient transport\u003csup\u003e74\u003c/sup\u003e. For visualizing the association or interaction of AEVs with host cells, AEVs of \u003cem\u003eM. smithii\u003c/em\u003e ALI, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, M. intestini, and \u003cem\u003eM. stadtmanae\u003c/em\u003e were incubated with macrophage monolayers (THP1-b) for 24 h and their localization was assessed by immunofluorescence microscopy. Co-localization of DiO-labeled AEVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-E, green dye) with and within host cell nuclei were investigated using the nuclei marker Hoechst 33342 (blue), and the cytoskeleton marker Alexa 647-Phalloidin (red). AEVs from all strains were shown to be in close association with the nuclei. Similar localization of EVs was previously described for bacterial EVs e.g. from \u003cem\u003eB. thetaiotaomicron\u003c/em\u003e\u003csup\u003e75\u003c/sup\u003e. A representative z-stack of \u003cem\u003eM. stadtmanae\u003c/em\u003e AEVs and macrophage monolayers supports the uptake of AEVs by the macrophage cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAEVs of M. intestini induce substantial IL-8 excretion in HT29 epithelial cell line\u003c/p\u003e \u003cp\u003eHuman intestinal HT-29 cells are useful for epithelial cell research, and have recently been used in a comparative study to assess the differential pro-inflammatory potency of BEVs derived from gut bacteria\u003csup\u003e25\u003c/sup\u003e. To investigate the pro-inflammatory potential of AEVs, we examined the IL-8 cytokine response in intestinal epithelial cells upon exposure to AEVs derived from \u003cem\u003eM. smithii\u003c/em\u003e ALI, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, M. intestini, and \u003cem\u003eM. stadtmanae\u003c/em\u003e. The pro-inflammatory cytokine IL-8 was chosen as it demonstrated a robust BEV-dependent induction in a previous study \u003csup\u003e25\u003c/sup\u003e. Moreover, BEVs of enterotoxigenic \u003cem\u003eEscherichia coli\u003c/em\u003e (ETEC) and \u003cem\u003eB. fragilis\u003c/em\u003e were included as representatives of intestinal BEVs known to induce a very high or no IL-8 response \u003csup\u003e25\u003c/sup\u003e. In concordance to a recent report\u003csup\u003e76\u003c/sup\u003e, AEVs derived from \u003cem\u003eM. smithii\u003c/em\u003e ALI, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, and \u003cem\u003eM. stadtmanae\u003c/em\u003e failed to induce a significant increase of the IL-8 levels compared to the no treatment control (NTC, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). In contrast, exposure of HT-29 cells to AEVs derived from M. intestini resulted in a significant IL-8 induction (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) at similar levels as observed for BEVs from ETEC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These results suggest that AEVs derived from different archaeal species demonstrate differential pro-inflammatory potency in HT-29 cells with AEVs from M. intestini inducing a relatively strong IL-8 response.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe discovery of archaeal extracellular vesicles (AEVs) produced by human GIT-associated archaea introduces a novel principle in archaea-microbiota and archaea-host interactions. Just like bacterial extracellular vesicles (BEVs) known from the human gut microbiota, AEVs are membrane-bound structures that transport various biomolecules, including proteins, lipids, and nucleic acids\u003csup\u003e4,8\u0026ndash;12\u003c/sup\u003e. We assume that these vesicles as well, have the potential to modulate the microbial community and host physiology, by acting as a communication and cargo vehicle.\u003c/p\u003e \u003cp\u003eThis study demonstrates that AEVs derived from GIT-associated archaea are comparable in size to BEVs, although the particle count was substantially lower for archaea (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Previous research has indicated that growth conditions, such as growth stage and medium composition, can influence the particle count, size, and vesicle cargo of BEVs leading to a heterogeneity among BEVs\u003csup\u003e13,29,77\u0026ndash;82\u003c/sup\u003e. It is likely that similar effects occur with AEVs. As we used biological replicates in our experiments, a certain fluctuation in e.g. metabolite cargo was observed. Heterogeneity implies that different vesicle subtypes may carry distinct cargo, potentially leading to varied biological effects by targeting different host cells or microbial cells\u003csup\u003e83\u0026ndash;85\u003c/sup\u003e. Moreover, the isolation process itself might impact the retrieval of different vesicle subtypes\u003csup\u003e83\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBoth studied archaeal genera (\u003cem\u003eMethanobrevibacter\u003c/em\u003e and \u003cem\u003eMethanosphaera\u003c/em\u003e) were capable of vesicle formation. All vesicles were found to be acquired by human monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), and stimulate IL-8 secretion (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). For detailed proteomic and metabolomic studies, this study focused on vesicles from \u003cem\u003eMethanobrevibacter\u003c/em\u003e species, the most abundant archaea in the human gut microbiome, comprising up to 4% of the microbiome\u003csup\u003e86\u003c/sup\u003e. \u003cem\u003eMethanobrevibacter\u003c/em\u003e species rely on syntrophic bacterial partners that provide small organic compounds like H\u003csub\u003e2\u003c/sub\u003e (or formate) and CO\u003csub\u003e2\u003c/sub\u003e for methanogenesis\u003csup\u003e63,87,88\u003c/sup\u003e. The bacterial partner benefits from this interaction, as potentially inhibiting end products of fermentation are efficiently removed\u003csup\u003e63,87,88\u003c/sup\u003e. As such, a well-regulated and controlled interaction with bacterial syntrophic partners is highly crucial for \u003cem\u003eMethanobrevibacter\u003c/em\u003e species.\u003c/p\u003e \u003cp\u003eAdhesins, which were found to be highly accumulated in archaeal vesicles, have been identified to be important communication vehicles. For instance, \u003cem\u003eMethanobrevibacter\u003c/em\u003e influences the metabolism of \u003cem\u003eChristensenella minuta\u003c/em\u003e, shifting short-chain fatty acid (SCFA) production from butyrate to acetate\u003csup\u003e89\u003c/sup\u003e. This complex communication system, regulating the metabolic processes of both partners, is believed to be mediated by \u003cem\u003eMethanobrevibacter\u003c/em\u003e surface adhesins, leading to significant physiological changes in the involved microorganisms\u003csup\u003e89\u003c/sup\u003e. From the bacterial kingdom, numerous adhesins are known to mediate interaction, colonization, infection and host interaction, making them key targets in bacterial pathogenesis\u003csup\u003e90,91\u003c/sup\u003e. Considering that adhesins are highly enriched in AEVs, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-D, the importance of AEVs for archaeal-bacterial and archaeal-host interactions over longer distances becomes evident.\u003c/p\u003e \u003cp\u003eIn \u003cem\u003eMethanobrevibacter ruminantium\u003c/em\u003e, a prevalent \u003cem\u003eMethanobrevibacter\u003c/em\u003e species in ruminants, 5% of the genome encodes adhesins. Among them, adhesin Mru_1499 has been identified as a crucial factor allowing \u003cem\u003eM. ruminantium\u003c/em\u003e M1 to bind and interact with hydrogen-producing protozoa and bacteria (i.e. \u003cem\u003eButyrivibrio proteoclasticus\u003c/em\u003e) in the rumen, facilitating efficient methane production\u003csup\u003e62\u003c/sup\u003e. Other adhesins facilitate adhesion to host cells and tissues, allowing microorganisms to establish and persist within the host environment.\u003c/p\u003e \u003cp\u003eNext to the upregulation of adhesins upon syntrophic interactions with hydrogen-producing microorganisms, adhesins were found to be increased also under nicotinic acid limitation (vitamin B3)\u003csup\u003e62,92,93\u003c/sup\u003e, indicating a complex interplay of metabolite-availability and the need for interaction with the microbial community and/ or the host.\u003c/p\u003e \u003cp\u003eEnriching adhesins on mobile vehicles such as AEVs offers numerous benefits, including the ability to reach communication partners beyond the immediate physical proximity of the non-motile archaeal cells potentially enabling even a global regulation of bacterial metabolism.\u003c/p\u003e \u003cp\u003eIt must be considered that also the host is a target of the AEVs, as indicated by the efficient uptake of AEVs in human monocytes, and the profound response of epithelial cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). It shall be mentioned that archaeal adhesins are believed to be heavily glycosylated\u003csup\u003e94\u003c/sup\u003e. Glycosylation is often species-specific, which could explain the different responses of HT-29 cells to AEVs from \u003cem\u003eMethanobrevibacter smithii\u003c/em\u003e ALI and Methanobrevibacter intestini, despite similar overall AEV assembly (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This highlights the importance of studying adhesin glycosylation patterns to understand their role in host-microbe interactions.\u003c/p\u003e \u003cp\u003eThe metabolic profiling of AEVs indicates increased levels of aspartic acid and glutamate (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which is intriguing and warrants further investigation. These findings suggest a potential link between AEVs and the gut-brain axis (as discussed in the \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003eresults\u003c/span\u003e section), opening new avenues for research into how these vesicles might influence host physiology and neurological processes.\u003c/p\u003e \u003cp\u003eMoreover, AEVs might possess similar capabilities to BEVs. In fact, BEVs have been shown to be able to interact with neighboring cells, cross the intestinal barrier, and enter the bloodstream, potentially reaching distant tissues, including the brain\u003csup\u003e10,95\u003c/sup\u003e. These traits can be exploited to use AEVs as potential next-generation drug delivery vehicles or targeted delivery systems, as has been already shown before by EVs of probiotic bacteria\u003csup\u003e96\u0026ndash;98\u003c/sup\u003e. In addition, similar to BEVs, AEVs could also serve as potential postbiotics, substances comprising inactivated microbes and/or their components that confer beneficial effects on the host\u003csup\u003e99\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn summary, the identification of AEVs and their components provides significant insights into the complex interactions within the gut microbiome, highlighting the critical role of \u003cem\u003eMethanobrevibacter\u003c/em\u003e adhesins in microbial communication and host interaction. This understanding could pave the way for novel therapeutic strategies targeting microbial interactions and their impacts on host health.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eRecent investigations have expanded our understanding of EVs beyond the bacterial domain, revealing their presence and significance in other microbial realms. Notably, the human archaeome, comprising archaeal communities inhabiting various niches within the human body, has emerged as a newfound player in the EV landscape. Archaea, once predominantly studied in extreme environments, have now been recognized as integral components of the human microbiota, exerting subtle yet profound influences on human health and disease.\u003c/p\u003e \u003cp\u003eThe revelation of EV production by the human archaeome introduces a new dimension to our comprehension of microbial communication within the human body. While the specific roles and functions of archaeal EVs remain largely unexplored, their existence suggests an intricate network of interdomain interactions shaping the dynamics of the human microbiome. Furthermore, the similarities and distinctions between bacterial and archaeal EVs present intriguing avenues for comparative studies, offering insights into the evolutionary origins and adaptive strategies of extracellular vesicle-mediated communication in diverse microbial taxa.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eSource of microorganisms.\u003c/p\u003e \u003cp\u003eThe human gut derived strains \u003cem\u003eMethanobrevibacter smithii\u003c/em\u003e ALI (DSM 2375), and \u003cem\u003eMethanosphaera stadtmanae\u003c/em\u003e (DSM 3091, type strain) were obtained from the German Collection of Microorganisms and Cell Cultures (DSMZ) GmbH, Braunschweig, Germany. \u003cem\u003eCandidatus\u003c/em\u003e M. intestini WWM1085 (DSM 116060) was obtained from the Department of Microbiology, University of Illinois, USA, where it was isolated from a stool sample of a healthy woman\u003csup\u003e24\u003c/sup\u003e. In the following, we will use the abbreviation \u0026ldquo;M. intestini\u0026rdquo; instead of \u003cem\u003eCandidatus\u003c/em\u003e M. intestini.\u003c/p\u003e \u003cp\u003e \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2 (DSM 116045) was isolated in 2018 at the Medical University of Graz, Graz, Austria, from a stool sample of a healthy woman\u003csup\u003e24\u003c/sup\u003e. Instead of opting for the \u003cem\u003eMethanobrevibacter smithii\u003c/em\u003e type strain (PS, DSM 861), our choice was \u003cem\u003eM. smithii\u003c/em\u003e ALI, as it sourced from a human fecal sample and not from sewage water. Enterotoxigenic \u003cem\u003eEscherichia coli\u003c/em\u003e (ETEC) H10407 and \u003cem\u003eBacteroides fragilis\u003c/em\u003e ATCC\u0026reg; 25285 have been reported previously\u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGrowth media and cultivation.\u003c/p\u003e \u003cp\u003eFor the cultivation of all methanogens standard methanogenium medium (MS) with some modifications as previously described \u003csup\u003e24\u003c/sup\u003e. For vesicle production, aliquots of 250 ml media in 1000 ml infusion bottles were sealed, pressurized with H\u003csub\u003e2\u003c/sub\u003e/CO\u003csub\u003e2\u003c/sub\u003e (4:1) and autoclaved. Before inoculation and incubation at 37\u0026deg;C, sodium acetate (0.001g/ml, anoxic, sterile) and yeast extract (0.001g/ml, anoxic, sterile, YE) were added to the media. Vesicles of ETEC and \u003cem\u003eB. fragilis\u003c/em\u003e were retrieved from stocks prepared earlier \u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eElectron microscopy\u003c/p\u003e \u003cp\u003eElectron microscopy (EM) was undertaken at the Core Facility Ultrastructure Analysis, Medical University of Graz, Graz, Austria and at the Core Science Resources Quadram Institute Bioscience, Norwich, United Kingdom. For ultrastructural analyses of cells, isolates were cultivated in 20 ml aliquots in 100 ml serum bottles for 7 days under anaerobic conditions at 37\u0026deg;C in an incubation shaker (shaking speed: 80 rpm). Followed by the centrifugation of 2 ml of medium containing each strain at 4000 g, 4\u0026deg;C, for 10 min. Cell pellets were then directly handed over to the Core Facility Ultrastructures, Medical University Graz, Graz, Austria for further preparation. AEVs (1x10\u003csup\u003e11\u003c/sup\u003e/ml) were directly handed over to the Core Science Resources Quadram Institute Bioscience, Norwich, United Kingdom.\u003c/p\u003e \u003cp\u003eTransmission electron microscopy: thin sections and tomography\u003c/p\u003e \u003cp\u003eCells were fixed in 2.5% (w/v) glutaraldehyde and 2% (w/v) paraformaldehyde in 0.1 M cacodylate buffer, pH 7.4, for 1 h, postfixed in 1% (w/v) osmium tetroxide for 2 h at room temperature, dehydrated in graded series of ethanol and embedded in TAAB (Agar Scientific, Essex, GB) epoxy resin. Ultrathin sections (70 nm thick) were cut with a UC 7 Ultramicrotome (Leica Microsystems, Vienna, Austria) and stained with lead citrate for 5 min and with platinum blue for 15 min. Images were taken using a Tecnai G2 20 transmission electron microscope (Thermo Fisher) with a Gatan ultrascan 1000 charge coupled device (CCD) camera (temperature \u0026minus;\u0026thinsp;20\u0026deg;C; acquisition software Digital Micrograph; Gatan, Munich, Germany). The acceleration voltage was 120 kV. The tilt series was reconstructed using FLARA, a joint alignment and reconstruction algorithm for electron tomography. This iterative algorithm allows for acquisitions without fiducial gold markers, since an effective shift computation can be obtained by using a global alignment technique based on a linearized approximation of the disruptive shifts in each iteration26. For negative staining cell suspensions were placed on glow discharged carbon coated copper grids for 1 min. The solution was removed after incubation by filter paper stripes. A drop of 1% aqueous uranyl acetate solution was placed afterwards for 1 min, dried with filter paper and later on air dried at room temperature. Specimens were examined with an FEI Tecnai G 2 (FEI, Eindhoven, Netherlands) equipped with a Gatan ultrascan 1000 charge coupled device (CCD) camera (-20\u0026deg;C, acquisition software Digital Micrograph, Gatan, Munich, Germany).\u003c/p\u003e \u003cp\u003eAEV suspensions were visualized using negative staining with TEM. Briefly, 4 \u0026micro;L AEV suspension was adsorbed to plasma-pretreated carbon-coated copper EM grids (EM Solutions) for 1 min before wicking off with filter paper and negatively staining with 1% Uranyl Acetate solution (BDH 10288) for 1 min. Grids were air-dried before analysis using a FEI Talos F200C electron microscope at 36,000\u0026times;-92,\u0026times;000 magnification with a Gatan OneView digital camera.\u003c/p\u003e \u003cp\u003eScanning electron microscopy\u003c/p\u003e \u003cp\u003eFor scanning electron microscopy, cells were affixed to coverslips and treated with a fixing solution consisting of 2% paraformaldehyde and 2.5% glutaraldehyde in 0.1 M phosphate buffered saline (pH 7.4). Subsequently, a graded ethanol series was used for dehydration. Post-fixation involved 1% Osmium tetroxide for 1 hour at room temperature, followed by additional dehydration in an ethanol series (ranging from 30\u0026ndash;100% EtOH). Hexamethyldisilazane (HMDS) was applied, and coverslips were positioned on stubs using conductive double-coated carbon tape. Imaging was performed with a Sigma 500VP FE-SEM equipped with a SEM Detector (Zeiss Oberkochen) operating at an acceleration voltage of 5 kV.\u003c/p\u003e \u003cp\u003eAEV Isolation\u003c/p\u003e \u003cp\u003eTo obtain a sufficient amount of biomass for the isolation of AEVs, 250 ml of MS medium was aliquoted into 1000 ml infusion bottles (VWR) and further handled the same way as described above. These cultures were then cultivated for 10 days under anaerobic conditions at 37\u0026deg;C in an incubation shaker (shaking speed: 80 rpm). When the pressure of cultivation bottles dropped due to growth, they were re-gassed with H\u003csub\u003e2\u003c/sub\u003e/CO\u003csub\u003e2\u003c/sub\u003e. Growth was surveyed by optical density photometry at 600 nm. On day ten, the cell suspensions were centrifuged at 14,000 x g, 4\u0026deg;C, 20 min (Thermo Scientific\u0026trade; Sorvall\u0026trade; LYNX\u0026trade; 6000). To remove cell debris and remaining cells, the supernatant was filtered with 0.22 \u0026micro;m PES bottle-top filters (Fisherbrand\u0026trade; Disposable PES Bottle Top Filters). If not immediately processed, the supernatant containing the vesicles was stored at 4\u0026deg;C.\u003c/p\u003e \u003cp\u003eIsolation of vesicles was done according to Stentz et al.\u003csup\u003e27\u003c/sup\u003e (Workflow see Supplementary Fig S1). In brief, a filtration cassette (Vivaflow 50R, 100,000 MWCO, Hydrostat, model VF05H4, Sartorius or Vivaflow 200 100,00 MWCO, PES, model VF20P4) was used to concentrate 1 L of sample down to approx. 5 ml. Then, 500 ml PBS buffer (pH 7.4) was added for washing purposes, and the liquid was concentrated to 1\u0026ndash;4 ml. The sample was then centrifuged for 20 min at 10,000 g, 4\u0026deg;C to remove protein and lipid aggregates. Next, the sample was transferred to Pierce\u0026trade; Protein Concentrators (PES, 100,000 MWCO, Thermo Scientific) and centrifuged at 3,000 g until the samples were concentrated down to 1 ml. Residual contaminants and proteins were further eliminated through size exclusion chromatography (SEC) using an IZON qEV1 column (pore size 35 mm) according to the manufacturer\u0026rsquo;s instructions. The vesicles were eluted in the 2.8 ml fraction containing the purified extracellular vesicles underwent a final filter sterilization using a 0.22 \u0026micro;m syringe filter (ROTILABO\u0026reg; PES, 0,22 \u0026micro;m), and were subsequently stored at 4\u0026deg;C until further use.\u003c/p\u003e \u003cp\u003eTo ensure that the final AEV suspension does not contain any yeast vesicles or other residues, the YE was sterile-filtered previous to medium preparation.\u003c/p\u003e \u003cp\u003eFor the metabolomics analyses, 1 L of blank MS medium underwent the same procedure to serve as a control.\u003c/p\u003e \u003cp\u003eBEV Isolation\u003c/p\u003e \u003cp\u003eBEVs for the HT-29 experiment were isolated as described previously with minor modifications\u003csup\u003e25,28\u003c/sup\u003e. Briefly, overnight cultures were either grown with aeration (180 rpm, Infor shaker) in case of ETEC or anaerobically (GasPak\u0026trade; EZ Systems, BD) in case of \u003cem\u003eB. fragilis\u003c/em\u003e to ensure sufficient growth. The respective cultures were diluted (1:100) in BHI medium and grown at 37\u0026deg;C either with aeration for 8 h or overnight anaerobically (GasPak\u0026trade; EZ Systems, BD). The cells were then removed from the supernatant by centrifugation (9,000 x g, 15 min) and subsequent sterile filtration (0.22 \u0026micro;m). The BEVs present in the supernatant were pelleted through subsequent ultracentrifugation (150,000 x g, 4\u0026deg;C, 4 h), resuspended in appropriate volumes of PBS to generate a BEV suspension 1000-fold more concentrated than in the original culture supernatant. Quantification and size distribution of BEVs were investigated by nanoparticle tracking analysis (NTA) using a Nanosight NS300 (see below).\u003c/p\u003e \u003cp\u003eAEV characterization\u003c/p\u003e \u003cp\u003eNanoparticle tracking analysis (NTA)\u003c/p\u003e \u003cp\u003eQuantification and size distribution of AEVs were investigated by nanoparticle tracking analysis (NTA) using ZetaView and Nanosight NS300. ZetaView was used by following established protocols\u003csup\u003e27,29\u003c/sup\u003e. In brief, particles were quantified using the ZetaView instrument (Particle Metrix, Germany) with ZetaView (version 8.05.12 SP1) software running a 2 cycle 11 position high frame rate analysis at 25\u0026deg;C. Samples were diluted with ultrapure water allowing the optimal detection range. Camera control settings: 80 Sensitivity; 30 Frame Rate; 100 Shutter. Post-acquisition parameters: 20 Min Brightness; 2000 Max Area; 5 Min Area; 30 Trace Length; 5 nm/Class; 64 Classes/Decade.\u003c/p\u003e \u003cp\u003eFor NanoSight NS300 (Malvern Instruments, UK) samples were diluted in 1x PBS according to the manufacturer\u0026rsquo;s guidelines (final concentration between 10\u003csup\u003e7\u003c/sup\u003e \u0026minus;\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e particles per ml), and a 405 nm laser was used. Between samples, the instrument was flushed with 10% Ethanol and Aqua.dest. Reads of 1-minute duration were performed in five replicates for each sample with the following capture settings: cell temperature: 25\u0026deg;C, syringe load/flow rate: 30, camera: sCMOS. For capture settings, camera level was adjusted so that all particles were distinctly visible (Camera level 12\u0026ndash;15). The ideal detection threshold was set including as many particles as possible and debris (blue cross count) with a maximum of five (detection threshold 5). Data output was acquired using NanoSight NTA software version 3.3 (Malvern Instruments). For each sample, the mean particle number in the Experiment Summary output was adjusted by the dilution factor.\u003c/p\u003e \u003cp\u003eProtein, DNA, and RNA content\u003c/p\u003e \u003cp\u003eAs previously described\u003csup\u003e30\u0026ndash;34\u003c/sup\u003e, quantification of vesicle content, including protein, DNA, and RNA, was conducted using the Qubit\u0026reg; Protein Assay, Qubit\u0026reg; dsDNA high sensitivity assay, and RNA high sensitivity assay kits, respectively (Thermo Fisher Scientific). Protein, DNA, and RNA measurements were performed using a Qubit\u0026reg; 4 or Qubit\u0026reg; 3 Fluorometer. Instructions of the manufacturer were followed.\u003c/p\u003e \u003cp\u003eLipid content\u003c/p\u003e \u003cp\u003eThe quantification of lipid content in AEVs was conducted using the FM4-64 lipophilic fluorescent dye and a linoleic acid standard, a method previously employed for bacterial extracellular vesicle (BEV) lipid quantification\u003csup\u003e35\u003c/sup\u003e. The modified procedure for quantifying vesicles released in culture was previously described in Juodeikis et al.\u003csup\u003e29\u003c/sup\u003e and includes the following steps: In duplicate, 20 \u0026micro;L of 30 \u0026micro;g/ml FM4-64 (Thermo Fisher Scientific) was combined with 180 \u0026micro;L of filtered culture supernatant or a linoleic acid standard in water (100, 75, 50, 20, 10, 5, 1, 0 \u0026micro;g/ml, prepared from a 1 mg/ml stock) in black 96-well plates. Following a 10-minute incubation at 37\u0026deg;C, endpoint fluorescence was analyzed using the FLUOStar Omega microplate reader with pre-set FM 4\u0026ndash;64 settings (Excitation: 515\u0026thinsp;\u0026minus;\u0026thinsp;15; Dichroic: auto 616.2; Emission 720\u0026thinsp;\u0026minus;\u0026thinsp;20), employing an enhanced dynamic range. Linear standard curves from the linoleic acid samples were established for lipid quantification.\u003c/p\u003e \u003cp\u003eProteomics\u003c/p\u003e \u003cp\u003eProtein profiles of whole cell lysates (WCL) and AEVs were analyzed. Therefore, 20 mg of cell biomass (3 replicates per species) were subjected to extensive ultrasonication with 400 \u0026micro;l of PBS. Cell debris was removed with centrifugation at 800 g at 4\u0026deg;C, for 5 min. The supernatants were collected for proteomic analysis. The protein content of the whole cell lysate was determined by Pierce BCA protein assay according to the manufacturer's protocol (Thermo, USA). Protein concentration of AEVs was measured by Qubit\u0026reg; Protein Assay (Thermo Fisher Scientific), as described above.\u003c/p\u003e \u003cp\u003eMass spectrometry analysis\u003c/p\u003e \u003cp\u003eFor LC-MS/MS analysis, 2 (for AEVs) or 5 \u0026micro;g (for WCLs) of protein were reduced and alkylated for 10 min at 95\u0026deg;C with final 10 mM TCEP (tris(2-carboxyethyl)phosphine) and 40 mM CAA (2-Chloroacetamide). The sample was processed according to the SP3 protocol\u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eand digested overnight with trypsin (Promega, enzyme/protein 1:50). Peptides were desalted using SBD-RPS tips as previously described\u003csup\u003e37\u003c/sup\u003e. 400 ng per sample (re-dissolved in 2% acetonitrile/0.1% formic acid in water) was subjected to LC-MS/MS analysis. Protein digests were separated by nano-HPLC (Dionex Ultimate 3000, Thermo Fisher Scientific(Dionex Ultimate 3000) equipped with a C18, 5 \u0026micro;m, 100 \u0026Aring;, 100 \u0026micro;m x 2 cm enrichment column and an Acclaim PepMap RSLC nanocolumn (C18, 2 \u0026micro;m, 100 \u0026Aring;, 500 x 0.075 mm) (all Thermo Fisher Scientific, Vienna, Austria). Samples were concentrated on the enrichment column for 5 min at a flow rate of 15 \u0026micro;l/min with 0.1 %formic acid as isocratic solvent. Separation was carried out on the nanocolumn at a flow rate of 300 nl/min at 60\u0026deg;C using the following gradient, where solvent A is 0.1 %formic acid in water and solvent B is acetonitrile containing 0.1 %formic acid: 0\u0026ndash;5 min: 2 %B; 5-123 min: 2\u0026ndash;35 %B; 123\u0026ndash;124 min: 35\u0026ndash;95 %B, 124\u0026ndash;134 min: 95 %B; 134\u0026ndash;135 min: 2 %B; 135\u0026ndash;150 min: 2% B. The maXis II ETD mass spectrometer (Bruker Daltonics, Germany) was operated with the captive source in positive mode with the following settings: mass range: 200\u0026ndash;2000 m/z, 2 Hz, capillary 1,600 V, dry gas flow 3 L/min with 150\u0026deg;C, nanoBooster 0.2 bar, precursor acquisition control top 20 (collision induced dissociation (CID). The mass spectrometry proteomics data were deposited to the ProteomeXchange Consortium\u003csup\u003e38\u003c/sup\u003e via the partner repository with the dataset identifier PXD053245 (Reviewer access details: Log in to the PRIDE website using the following details: PDX accession: PXD053245;Username: \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\[email protected]\u003c/span\u003e; Password: MFqECDz7Uyv6)\u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe LC-MS/MS data were analyzed by MSFragger\u003csup\u003e39,40\u003c/sup\u003e by searching the public \u003cem\u003eMethanobrevibacter\u003c/em\u003e protein databases (UP000232133; UP000003489; UP000004028; UP000018189; UP000001992), the archaeal protein catalogue described in Chibani et al.\u003csup\u003e22\u003c/sup\u003e and a list of common contaminants\u003csup\u003e41\u003c/sup\u003e. Additional information on proteins found in all vesicles was retrieved via MaGe\u003csup\u003e42\u003c/sup\u003e and the implemented functions SignalP (version 4.1)\u003csup\u003e43\u003c/sup\u003e, MHMM (version 2.0c)\u003csup\u003e44,45\u003c/sup\u003e and InterProScan\u003csup\u003e46,47\u003c/sup\u003e, as well as from the InterPro Database\u003csup\u003e47\u003c/sup\u003e (Supplementary Table\u0026nbsp;5).\u003c/p\u003e \u003cp\u003eCarbamidomethylation of cysteine and oxidation on methionine were set as a fixed and as a variable modification, respectively. Detailed search criteria were used as follows: trypsin, max. missed cleavage sites: 2; search mode: MS/MS ion search with decoy database search included; precursor mass tolerance\u0026thinsp;\u0026plusmn;\u0026thinsp;20 ppm; product mass tolerance\u0026thinsp;\u0026plusmn;\u0026thinsp;15 ppm; acceptance parameters for identification: 1% protein FDR\u003csup\u003e48\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eData from EV and whole cell lysates were processed with Perseus software version 1.6.15.0. Data was filtered for decoy hits and contaminants. After log2 transformation, and subtracting the median from the column proteins were filtered for containing at least 2 valid values in at least one group.\u003c/p\u003e \u003cp\u003eMass spectrometry derived AEV metabolomics\u003c/p\u003e \u003cp\u003eBiological triplicates of the vesicle preparations were used for the LC-MS analysis, and a technical duplicate of a non-cultured medium that had passed through the pipeline for vesicle isolation was used as a medium blank. All samples were stored at -70\u0026deg;C until processing at the Vienna BioCenter Metabolomics Core Facility.\u003c/p\u003e \u003cp\u003eThe samples were diluted with 50 \u0026micro;L ACN and subjected to analysis with liquid chromatography-mass spectrometry (LC-MS). 11 \u0026micro;L of each sample was pooled and used as a quality control (QC) sample. Samples were randomly injected on an iHILIC\u0026reg;-(P) Classic HPLC column (HILICON AB, 100 x 2.1 mm; 5 \u0026micro;m; 200 \u0026Aring;, Sweden) with a flow rate of 100 \u0026micro;L/min delivered through an Ultimate 3000 HPLC system (Thermo Fisher Scientific, Germany). The stepwise gradient has a total run time of 35 min, starts at 90% A (ACN), and takes 21 min to 60% B (25 mM ammonium bicarbonate) followed by 5 min hold at 80% B and a subsequent equilibration phase at 90%. The LC was coupled to a high-resolution tandem MS instrument (Q-Exactive Focus, Thermo Fisher Scientific, Germany). The ionization potential was set to +\u0026thinsp;3.5/-3.0 kV, the sheet gas flow to 20, and an auxiliary gas flow of 5 was used. Samples were flanked by a blank and a QC sample for background labeling and data normalization, respectively.\u003c/p\u003e \u003cp\u003eThe obtained data set was processed by \u0026ldquo;Compound Discoverer 3.3 SP2\u0026rdquo; (Thermo Fisher Scientific). Annotation of the compounds was done through searching against our internal mass list database generated with authentic standard solutions (highest confidence level). Additionally, the mzCloud database was searched for fragment matching and ChemSpider hits were obtained using BioCyc, Human Metabolome Database, \u003cem\u003eE. coli\u003c/em\u003e Metabolome Database, and KEGG databases. Only metabolites identified with highest confirmation (match with internal database) were examined in more detail; additional ones are provided in Supplementary Table\u0026nbsp;7).\u003c/p\u003e \u003cp\u003eThe log2 fold changes, as well as p-values, were calculated by the Compound Discoverer software (Tukey HSD test (posthoc), after an analysis of variance (ANOVA) test).\u003c/p\u003e \u003cp\u003eCo-incubation experiments with cell lines\u003c/p\u003e \u003cp\u003eCytotoxicity tests of AEVs and BEVs\u003c/p\u003e \u003cp\u003e3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) cell viability assays were routinely performed at the end of the HT-29 cell culture assays\u003csup\u003e49\u003c/sup\u003e, but no significant reduction in metabolic activity could be observed for any condition used in this study (data not shown).\u003c/p\u003e \u003cp\u003eAdditionally, CellTiter-Glo\u0026reg; 2.0 Cell Viability Assay (Promega) was used to investigate the cytotoxicity of AEVs on THP1-Blue cells, but no reduction in the viable cells could be detected (data not shown).\u003c/p\u003e \u003cp\u003eConfocal Microscopy\u003c/p\u003e \u003cp\u003e \u003cem\u003eM. smithii\u003c/em\u003e ALI, M. intestini, \u003cem\u003eM. smithii\u003c/em\u003e GRAZ-2, and \u003cem\u003eM. stadtmanae\u003c/em\u003e-derived AEVs (1x10\u003csup\u003e11\u003c/sup\u003e/ml) were labeled with 5% DiO at 37\u0026deg;C for 30 minutes. Labeled DiO - AEVs (1x10\u003csup\u003e11\u003c/sup\u003e/well [10 \u0026micro;l]) were added to THP1-b cell monolayers cultured on collagen solution (Merck) coated 12-well chamber slides (IBIDI) overnight (16 hrs). THP1-b monocytes were previously induced to differentiate into macrophages using 150 nM PMA (Phorbol 12-myristate 13-acetate; Sigma, P8139). Samples were fixed using Pierce 4% PFA (ThermoFisher), permeabilized with 0.25% Triton X1000 (Sigma), and blocked with 10% goat serum in PBS. For nuclear visualization, cells were incubated with Hoechst 33342 (ThermoFisher), Alexa 647-Phalloidin to visualize intracellular membranes. As a second approach, AEVs were incubated with Archaea specific primary antibodies (Davids Biotechnologie GmbH, affinity purified, specific for \u003cem\u003eMethanobrevibacter\u003c/em\u003e and \u003cem\u003eMethanosphaera\u003c/em\u003e) and AF647 as the secondary antibody, and cells were labeled with Hoechst 33342 (ThermoFisher). Images were taken using a Zeiss LSM880 confocal microscope equipped with a 63x/1.40 oil objective. Fluorescence was recorded at 405 (blue, nucleus), 488 (green, AEVs), and 594 nm (red, intracellular membranes or AEVs). The red channel was adjusted using the ZEISS ZEN 3.9 (ZEN lite) software by the best-fit function.\u003c/p\u003e \u003cp\u003eHT-29 cytokine release\u003c/p\u003e \u003cp\u003eThe HT-29 cytokine release assay was performed at the Institute of Molecular Biosciences, University of Graz. HT-29 (intestinal epithelial cells) were grown in T-175 tissue culture flask, containing Dulbecco's Modified Eagle's medium/ Nutrient F-12 (DMEM-F12) medium (Gibco, USA) supplemented with 10% fetal bovine serum (FBS), Penicillin-Streptomycin (100 \u0026micro;g/ml streptomycin and 100 Units/ml penicillin) and L-Glutamine (2 mM) at 37\u003csup\u003eo\u003c/sup\u003eC in a CO\u003csub\u003e2\u003c/sub\u003e incubator. To investigate the pro-inflammatory potency of AEVs and BEVs, HT-29 cells were seeded in a 24 well tissue culture plates at a concentration of 6 x 10\u003csup\u003e5\u003c/sup\u003e cells/well and cultivated for 24 h in DMEM-F12 medium supplemented with 10% fetal bovine serum (FBS), Penicillin-Streptomycin and L-Glutamine. Then, intestinal epithelial cells were washed once with PBS and the medium was replaced with AEVs or BEVs (10\u003csup\u003e8\u003c/sup\u003e particles/ ml) resuspended in DMEM-F12 medium without FBS. After incubation for 20 h the cell culture supernatant was harvested, centrifuged for 2500 rpm at 4\u0026deg;C for 10 min to remove the cell debris and stored at -20\u0026deg;C for subsequent Interleukin 8 (IL-8) quantification by ELISA, which was performed as previously described according to the manufacturer\u0026rsquo;s protocol\u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStatistics and data visualization\u003c/p\u003e \u003cp\u003eVesicle properties (Concentration, size, nucleic acids, and protein content) and metabolites were plotted as boxplots in R (R-Core-Team, 2024) using the ggplot2 Package (v3.5.1)\u003csup\u003e50\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCreation of Venn diagrams was performed by using the online tool interactiVenn\u003csup\u003e51\u003c/sup\u003e. PCA was created with Perseus software (v1.6.15.0)\u003csup\u003e52\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe overview of proteins identified in archaeal vesicles and whole cell lysates, as well as proteins annotated as adhesins, were displayed in heatmaps using ggplot2 (v3.5.1) \u003csup\u003e50\u003c/sup\u003e, with data transformation performed using the reshape2\u003csup\u003e53\u003c/sup\u003e package (v1.4.4; Wickham, 2007). Barchart of mean intensities of protein categories was plotted with ggplot2 (v3.5.1) \u003csup\u003e50\u003c/sup\u003e, and dplyr (v1.1.4)\u003csup\u003e54\u003c/sup\u003e was used for the calculation of mean and standard deviation. IL-8 excretion in the HT-29 cell line was visualized as a bar chart using ggplot2 (v3.5.1) \u003csup\u003e50\u003c/sup\u003e, with data transformation by reshape2\u003csup\u003e53\u003c/sup\u003e (v1.4.4; Wickham, 2007), FSA (v0.9.5)\u003csup\u003e55\u003c/sup\u003e, and ggsignif (v0.6.4)\u003csup\u003e56\u003c/sup\u003e. For IL-8 excretion Kruskal-Wallis test followed by Dunn\u0026rsquo;s Multiple comparison where all EV samples were compared to the NTC (no treatment control).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eNone declared.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded in whole or in part by the Austrian Science Fund (FWF) [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.55776/F83\u003c/span\u003e\u003cspan address=\"10.55776/F83\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.55776/P32697\u003c/span\u003e\u003cspan address=\"10.55776/P32697\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.55776/COE7\u003c/span\u003e\u003cspan address=\"10.55776/COE7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e]. The authors acknowledge the support of the ZMF Galaxy Team: Core Facility Computational Bioanalytics, Medical University of Graz, funded by the Austrian Federal Ministry of Education, Science and Research, Hochschulraum-Strukturmittel 2016 grant as part of BioTechMed Graz. The Vienna BioCenter Core Facilities (VBCF) Metabolomics Facility acknowledges funding from the Austrian Federal Ministry of Education, Science \u0026amp; Research; and the City of Vienna.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eThe study was designed by CME and VW. VW, PM, and TZ isolated the vesicles, together with help from RS, EJ, and SRC. Vesicle biophysical characterization was done by VW. VW and BD performed proteomics and analyzed the data with the supervision of HK and CME. Metabolomics was performed by TKoe and GG, and data were analyzed by VW and CME. Electron microscopy was performed by DP, KH, DK, and KG. HT and SS performed experiments with HT-29 cells. Experiments with macrophages were performed by VW, with the help of RS and EJ. The lipid assay was performed by RJ. VW and CME wrote the manuscript, and TS, CK, RM, TKue, and TW contributed to the writing of the manuscript and figure preparation. The manuscript was read and approved by all authors.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank Stefanie Duller for providing electron micrographs. The support for V. Weinberger through the local dissertation program MolMed is acknowledged. We acknowledge the JIC Bioimaging facility and staff for their contribution to this publication.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eAll original data are either provided in the supplementary information/ tables, and/or on our Github repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/vikwein/Archaeal_extracellular_vesicles\u003c/span\u003e\u003cspan address=\"https://github.com/vikwein/Archaeal_extracellular_vesicles\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGill S, Catchpole R, Forterre P (2019) Extracellular membrane vesicles in the three domains of life and beyond. 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ACS Nano 8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie J, Li Q, Nie S (2024) Bacterial extracellular vesicles: An emerging postbiotic. \u003cem\u003eTrends in Food Science and Technology\u003c/em\u003e vol. 143 Preprint at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tifs.2023.104275\u003c/span\u003e\u003cspan address=\"10.1016/j.tifs.2023.104275\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4687775/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4687775/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroorganisms thriving in the human gastrointestinal microbiome have developed numerous mechanisms for microbiome-host and microbe-microbe interaction, including the formation of extracellular vesicles (EVs). However, the interactive mechanisms of members of the human archaeome remained largely unexplored.\u003c/p\u003e \u003cp\u003eHere, we report the capability of two Methanobrevibacter strains M. smithii, Cand. M. intestini and Methanosphaera stadtmanae, to produce EVs. While the size (~\u0026thinsp;130 nm) and morphology of these archaeal EVs were comparable to bacterial EVs, proteomic and metabolomic analyses revealed unique traits. The proteins found in both the EVs of M. smithii and Cand. M. intestini (n\u0026thinsp;=\u0026thinsp;229) predominantly included adhesin and adhesin-like proteins, involved in archaea-surface and archaea-bacteria interaction. Additionally, the archaeal EVs contained glutamic acid and choline glycerophosphate, which could be involved in gut-brain signalling.\u003c/p\u003e \u003cp\u003eVesicles from all studied species were efficiently taken up by human monocytes and induced IL-8 production in epithelial HT-29 cells.\u003c/p\u003e \u003cp\u003eThe identification of archaeal EVs and their components provides novel insights into the complex interactions between the archaeal and bacterial microbiome and the host, potentially offering new paths to modulate vesicle-mediated impacts on host health.\u003c/p\u003e","manuscriptTitle":"Proteomic and Metabolomic Profiling of Archaeal Extracellular Vesicles from the Human Gut","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-17 10:43:41","doi":"10.21203/rs.3.rs-4687775/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"56ed8c5a-4c44-4bd2-a57d-97c0cd868d67","owner":[],"postedDate":"July 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":34633400,"name":"Biological sciences/Microbiology/Archaea/Archaeal biology"},{"id":34633401,"name":"Biological sciences/Biological techniques"}],"tags":[],"updatedAt":"2025-06-04T07:09:03+00:00","versionOfRecord":{"articleIdentity":"rs-4687775","link":"https://doi.org/10.1038/s41467-025-60271-w","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-06-03 04:00:00","publishedOnDateReadable":"June 3rd, 2025"},"versionCreatedAt":"2024-07-17 10:43:41","video":"","vorDoi":"10.1038/s41467-025-60271-w","vorDoiUrl":"https://doi.org/10.1038/s41467-025-60271-w","workflowStages":[]},"version":"v1","identity":"rs-4687775","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4687775","identity":"rs-4687775","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}