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Gut Microbiota‐Derived Extracellular Vesicles Influence Alcohol Intake Preferences in Rats
(Wiley, 2025-03)
Macarena Díaz‐Ubilla
;
Aliosha I. Figueroa‐Valdés
;
Hugo E. Tobar
;
María Elena Quintanilla
;
Eugenio Díaz
<jats:title>ABSTRACT</jats:title><jats:p>Growing preclinical and clinical evidence suggests a link between gut microbiota dysbiosis and problematic alcohol consumption. Extracellular vesicles (EVs) are key mediators involved in bacteria‐to‐host communication. However, their potential role in mediating addictive behaviour remains unexplored. This study investigates the role of gut microbiota‐derived bacterial extracellular vesicles (bEVs) in driving high alcohol consumption. bEVs were isolated from the gut microbiota of a high alcohol‐drinking rat strain (UChB rats), either ethanol‐naïve or following chronic alcohol consumption and administered intraperitoneally or orally to alcohol‐rejecting male and female Wistar rats. Both types of UChB‐derived bEVs increased Wistar's voluntary alcohol consumption (three bottle choice test) up to 10‐fold (<jats:italic>p</jats:italic> < 0.0001), indicating that bEVs are able and sufficient to transmit drinking behaviour across different rat strains. Molecular analysis revealed that bEVs administration did not induce systemic or brain inflammation in the recipient animals, suggesting that the increased alcohol intake triggered by UChB‐derived bEVs operates through an inflammation‐independent mechanism. Furthermore, we demonstrate that the vagus nerve mediates the bEV‐induced increase in alcohol consumption, as bilateral vagotomy completely abolished the high drinking behaviour induced by both intraperitoneally injected and orally administered bEVs. Thus, this study identifies bEVs as a novel mechanism underlying gut microbiota‐induced high alcohol intake in a vagus nerve‐dependent manner.</jats:p>
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Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results From a Preliminary Retrospective Study
(2022)
Shreyas V. Kumbhare
;
Patricia A. Francis-Lyon
;
Dashyanng Kachru
;
Tejaswini Uday
;
Carmel Irudayanathan
<jats:p>Diet and lifestyle-related illnesses including functional gastrointestinal disorders (FGIDs) and obesity are rapidly emerging health issues worldwide. Research has focused on addressing FGIDs via in-person cognitive-behavioral therapies, diet modulation and pharmaceutical intervention. Yet, there is paucity of research reporting on digital therapeutics care delivering weight loss and reduction of FGID symptom severity, and on modeling FGID status and symptom severity reduction including personalized genomic SNPs and gut microbiome signals. Our aim for this study was to assess how effective a digital therapeutics intervention personalized on genomic SNPs and gut microbiome signals was at reducing symptomatology of FGIDs on individuals that successfully lost body weight. We also aimed at modeling FGID status and FGID symptom severity reduction using demographics, genomic SNPs, and gut microbiome variables. This study sought to train a logistic regression model to differentiate the FGID status of subjects enrolled in a digital therapeutics care program using demographic, genetic, and baseline microbiome data. We also trained linear regression models to ascertain changes in FGID symptom severity of subjects at the time of achieving 5% or more of body weight loss compared to baseline. For this we utilized a cohort of 177 adults who reached 5% or more weight loss on the Digbi Health personalized digital care program, who were retrospectively surveyed about changes in symptom severity of their FGIDs and other comorbidities before and after the program. Gut microbiome taxa and demographics were the strongest predictors of FGID status. The digital therapeutics program implemented, reduced the summative severity of symptoms for 89.42% (93/104) of users who reported FGIDs. Reduction in summative FGID symptom severity and IBS symptom severity were best modeled by a mixture of genomic and microbiome predictors, whereas reduction in diarrhea and constipation symptom severity were best modeled by microbiome predictors only. This preliminary retrospective study generated diagnostic models for FGID status as well as therapeutic models for reduction of FGID symptom severity. Moreover, these therapeutic models generate testable hypotheses for associations of a number of biomarkers in the prognosis of FGIDs symptomatology.</jats:p>
30Scopus© Citations 12

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