Microbial Extracellular Vesicles Research Articles

Microbial extracellular vesicles contribute to antimicrobial resistance.

With the escalating global antimicrobial resistance crisis, there is an urgent need for innovative strategies against drug-resistant microbes. Accumulating evidence indicates microbial extracellular vesicles (EVs) contribute to antimicrobial resistance. Therefore, comprehensively elucidating the roles and mechanisms of microbial EVs in conferring resistance could provide new perspectives and avenues for novel antimicrobial approaches. In this review, we systematically examine current research on antimicrobial resistance involving bacterial, fungal, and parasitic EVs, delineating the mechanisms whereby microbial EVs promote resistance. Finally, we discuss the application of bacterial EVs in antimicrobial therapy.

Association between the Respiratory Microbiome and Plasma Microbial Extracellular Vesicles in Intubated Patients.

Extracellular vesicles (EVs) regulate various cellular and immunological functions in human diseases. There is growing interest in the clinical role of microbial EVs in pneumonia. However, there is a lack of research on the correlation between lung microbiome with microbial EVs and the microbiome of other body sites in pneumonia. We investigated the co-occurrence of lung microbiome and plasma microbe-derived EVs (mEVs) in 111 samples obtained from 60 mechanically ventilated patients (41 pneumonia and 19 non-pneumonia cases). The microbial correlation between the two samples was compared between the pneumonia and non-pneumonia cases. Bacterial composition of the plasma mEVs was distinct from that of the lung microbiome. There was a significantly higher correlation between lung microbiome and plasma mEVs in non-pneumonia individuals compared to pneumonia patients. In particular, Acinetobacter and Lactobacillus genera had high correlation coefficients in non-pneumonia patients. This indicates a beneficial effect of mEVs in modulating host lung immune response through EV component transfer.

Emerging therapeutic role of gut microbial extracellular vesicles in neurological disorders.

Extracellular vesicles (EVs) serve as cell-to-cell and inter-organ communicators by conveying proteins and nucleic acids with regulatory functions. Emerging evidence shows that gut microbial-released EVs play a pivotal role in the gut-brain axis, bidirectional communication, and crosstalk between the gut and the brain. Increasing pre-clinical and clinical evidence suggests that gut bacteria-released EVs are capable of eliciting distinct signaling to the brain with the ability to cross the blood-brain barrier, exerting regulatory function on brain cells such as neurons, astrocytes, and microglia, via their abundant and diversified protein and nucleic acid cargo. Conversely, EVs derived from certain species of bacteria, particularly from gut commensals with probiotic properties, have recently been shown to confer distinct therapeutic effects on various neurological disorders. Thus, gut bacterial EVs may be both a cause of and therapy for neuropathological complications. This review marshals the basic, clinical, and translational studies that significantly contributed to our up-to-date knowledge of the therapeutic potential of gut microbial-derived EVs in treating neurological disorders, including strokes, Alzheimer's and Parkinson's disease, and dementia. The review also discusses the newer insights in recent studies focused on developing superior therapeutic microbial EVs via genetic manipulation and/or dietary intervention.

Machine-learning algorithms for asthma, COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects

Although mounting evidence suggests that the microbiome has a tremendous influence on intractable disease, the relationship between circulating microbial extracellular vesicles (EVs) and respiratory disease remains unexplored. Here, we developed predictive diagnostic models for COPD, asthma, and lung cancer by applying machine learning to microbial EV metagenomes isolated from patient serum and coded by their accumulated taxonomic hierarchy. All models demonstrated high predictive strength with mean AUC values ranging from 0.93 to 0.99 with various important features at the genus and phylum levels. Application of the clinical models in mice showed that various foods reduced high-fat diet-associated asthma and lung cancer risk, while COPD was minimally affected. In conclusion, this study offers a novel methodology for respiratory disease prediction and highlights the utility of serum microbial EVs as data-rich features for noninvasive diagnosis.

Dietary protein increases T-cell-independent sIgA production through changes in gut microbiota-derived extracellular vesicles

Secretory IgA is a key mucosal component ensuring host-microbiota mutualism. Here we use nutritional geometry modelling in mice fed 10 different macronutrient-defined, isocaloric diets, and identify dietary protein as the major driver of secretory IgA production. Protein-driven secretory IgA induction is not mediated by T-cell-dependent pathways or changes in gut microbiota composition. Instead, the microbiota of high protein fed mice produces significantly higher quantities of extracellular vesicles, compared to those of mice fed high-carbohydrate or high-fat diets. These extracellular vesicles activate Toll-like receptor 4 to increase the epithelial expression of IgA-inducing cytokine, APRIL, B cell chemokine, CCL28, and the IgA transporter, PIGR. We show that succinate, produced in high concentrations by microbiota of high protein fed animals, increases generation of reactive oxygen species by bacteria, which in turn promotes extracellular vesicles production. Here we establish a link between dietary macronutrient composition, gut microbial extracellular vesicles release and host secretory IgA response.

Metagenomic Analysis of Plasma Microbial Extracellular Vesicles in Patients Receiving Mechanical Ventilation: A Pilot Study.

Background: Previous studies reported a significant association between pneumonia outcome and the respiratory microbiome. There is increasing interest in the roles of bacterial extracellular vesicles (EVs) in various diseases. We studied the composition and function of microbiota-derived EVs in the plasma of patients receiving mechanical ventilation to evaluate whether they can be used as a diagnostic marker and to predict clinical outcomes. Methods: Plasma samples (n = 111) from 59 mechanically ventilated patients (41 in the pneumonia group; 24 in the nursing home and hospital-associated infection [NHAI] group) were prospectively collected on days one and seven. After isolating the bacterial EVs from plasma samples, nucleic acid was extracted for 16S rRNA gene pyrosequencing. The samples were evaluated to determine the α and β diversity, bacterial composition, and predicted functions. Results: Principal coordinates analysis revealed significantly different clustering of microbial EVs between the pneumonia and non-pneumonia groups. The proportions of Lactobacillus, Cutibacterium, and Sphingomonas were significantly different between the pneumonia and non-pneumonia groups. In addition, the abundances of Lactobacillus and Bifidobacterium were significantly higher in the non-NHAI than the NHAI group. In the analysis of β diversity, the structure of microbial EVs differed significantly different between 28-day survivors and non-survivors (Bray-Curtis distance, p = 0.014). Functional profiling revealed significant differences between the pneumonia and non-pneumonia groups. The longitudinal change in predicted functions of microbial EV genes showed a significant difference between 28-day survivors and non-survivors. Conclusions: Bacterial microbiota–derived EVs in the plasma have potential as diagnostic and prognostic markers for patients receiving mechanical ventilation. Further large prospective studies are needed to determine the clinical utility of plasma microbiota-EVs in intubated patients.

Microbiome Markers of Pancreatic Cancer Based on Bacteria-Derived Extracellular Vesicles Acquired from Blood Samples: A Retrospective Propensity Score Matching Analysis.

Simple SummaryAlthough tremendous advances in diagnosis and treatment, pancreatic cancer still remains one of the lethal diseases with an overall survival rate of 10~15%. Early detection and diagnosis of pancreatic cancer is very important in improving the prognosis of patients. The aim of our study was to find new biomarkers, using microbiomes based on bacteria-derived extracellular vesicles, extracted from blood serum. With 38 patients with pancreatic cancer and 52 healthy controls with no history of pancreatic disease, we identified several compositional differences of microbiome between them. Using various combinations of the metagenomic markers which made the compositional differences, we also built a pancreatic cancer prediction model with high area under the receiver operating characteristic curve (0.966 at the phylum level and 1.000 at the genus level). These microbiome markers, based on bacteria-derived extracellular vesicles acquired from blood, show demonstrate the potential of candidate biomarkers for early diagnosis of pancreatic cancer.Novel biomarkers for early diagnosis of pancreatic cancer (PC) are necessary to improve prognosis. We aimed to discover candidate biomarkers by identifying compositional differences of microbiome between patients with PC (n = 38) and healthy controls (n = 52), using microbial extracellular vesicles (EVs) acquired from blood samples. Composition analysis was performed using 16S rRNA gene analysis and bacteria-derived EVs. Statistically significant differences in microbial compositions were used to construct PC prediction models after propensity score matching analysis to reduce other possible biases. Between-group differences in microbial compositions were identified at the phylum and genus levels. At the phylum level, three species (Verrucomicrobia, Deferribacteres, and Bacteroidetes) were more abundant and one species (Actinobacteria) was less abundant in PC patients. At the genus level, four species (Stenotrophomonas, Sphingomonas, Propionibacterium, and Corynebacterium) were less abundant and six species (Ruminococcaceae UCG-014, Lachnospiraceae NK4A136 group, Akkermansia, Turicibacter, Ruminiclostridium, and Lachnospiraceae UCG-001) were more abundant in PC patients. Using the best combination of these microbiome markers, we constructed a PC prediction model that yielded a high area under the receiver operating characteristic curve (0.966 and 1.000, at the phylum and genus level, respectively). These microbiome markers, which altered microbial compositions, are therefore candidate biomarkers for early diagnosis of PC.

Emerging role of bacterial extracellular vesicles in cancer.

Shedding of microbial extracellular vesicles constitutes a universal mechanism for inter-kingdom and intra-kingdom communication that is conserved among prokaryotic and eukaryotic microbes. In this review we delineate fundamental aspects of bacterial extracellular vesicles (BEVs) including their biogenesis, cargo composition, and interactions with host cells. We critically examine the evidence that BEVs from the host gut microbiome can enter the circulatory system to disseminate to distant organs and tissues. The potential involvement of BEVs in carcinogenesis is evaluated and future research ideas explored. We further discuss the potential of BEVs in microbiome-based liquid biopsies for cancer diagnostics and bioengineering strategies for cancer therapy.

Study of Microbial Extracellular Vesicles:Separation by Density Gradients, Protection Assays and Labelling for Live Tracking.

Extracellular vesicles (EVs) are produced by all domains of life including Bacteria, Archaea and Eukarya. EVs are critical for cellular physiology and contain varied cargo: virulence factors, cell wall remodeling enzymes, extracellular matrix components and even nucleic acids and metabolites. While various protocols for isolating EVs have been established for mammalian cells, the field is actively developing tools to study EVs in other organisms. In this protocol we describe our methods to perform density gradient purification of EVs in bacterial cells, allowing for separation of EV subpopulations, followed by protection assays for EV cargo characterization. Furthermore, we devised a protocol which incorporates a fluorescent conjugate of fatty acids into EVs, the first to allow live-cell EV tracking to observe release of EVs, including during infection of mammalian cells by pathogenic bacteria. These protocols are powerful tools for EV researchers as they enable the observation of EV release and the study of the mechanisms of their formation and release.

Consumption of a Leuconostoc holzapfelii-enriched synbiotic beverage alters the composition of the microbiota and microbial extracellular vesicles

Synbiotics, the combination of probiotics and prebiotics, are known to confer health benefits via intestinal microbiota modulation. However, significant intestinal microbiota alterations can be difficult to determine in intervention studies based on solely bacterial stool metagenomic analysis. Intestinal microbiota constituents secrete 20–200-nm-sized extracellular vesicles (EVs) containing microbial DNA, proteins, and lipids that are distributed throughout the body, providing an alternative target for microbiota metagenomic analysis. Here, we determined the impact of a synbiotic beverage enriched with the kimchi-derived bacterium Leuconostoc holzapfelii (L. holzapfelii) on the intestinal microbiota and local and circulatory microbiota-derived EV composition of healthy Korean adults. We isolated microbial DNA from stool bacteria, stool EVs, and urinary EVs and conducted next-generation sequencing of the 16S rDNA V3–V4 regions before and after synbiotic consumption. The species diversity of circulating urinary EVs was significantly increased after synbiotic consumption, while stool bacterial and EV diversity remained unchanged. Furthermore, we found that while a single genus was decreased among the stool bacteria constituents, stool EVs and urinary EVs showed significant alterations in four and eight genera, respectively. Blood chemistry assays revealed that synbiotic consumption significantly lowered aspartate aminotransferase (AST) serum levels, particularly in subjects with starting levels above the normal range (>40 UI/L). In conclusion, the L. holzapfelii-enriched synbiotic beverage greatly altered serum AST levels and microbial EV composition in urine and stool, while only minor changes were observed in the gut microbiota composition. Based on these findings, we suggest the potential use of microbiota-derived EVs as surrogate markers in future predictive diagnosis studies.