Colonic microbiota ferment non-absorbed dietary fiber to produce prodigious amounts of short chain fatty acids (SCFAs) that benefit the host through a myriad of metabolic, trophic, and chemopreventative effects. The chemopreventative effects of the SCFA butyrate are, in part, mediated through induction of p21 gene expression. In this study, we assessed the role of microRNA(miRNA) in butyrate's induction of p21 expression. The expression profiles of miRNAs in HCT-116 cells and in human sporadic colon cancers were assessed by microarray and quantitative PCR. Regulation of p21 gene expression by miR-106b was assessed by 3′ UTR luciferase reporter assays and transfection of specific miRNA mimics. Butyrate changed the expression of 44 miRNAs in HCT-116 cells, many of which were aberrantly expressed in colon cancer tissues. Members of the miR-106b family were decreased in the former and increased in the latter. Butyrate-induced p21 protein expression was dampened by treatment with a miR-106b mimic. Mutated p21 3′UTR-reporter constructs expressed in HCT-116 cells confirmed direct miR-106b targeting. Butyrate decreased HCT-116 proliferation, an effect reversed with the addition of the miR-106b mimic. We conclude that microbe-derived SCFAs regulate host gene expression involved in intestinal homeostasis as well as carcinogenesis through modulation of miRNAs.

Advances in sequencing technology and bioinformatics have greatly enhanced our ability to understand the human microbiome. Over the last decade, a growing body of literature has linked nutrition and the environment to the microbiome and is now thought to be an important contributor to overall health. This paper reviews the literature from the past 10 years to highlight the influence of environmental factors such as diet, early life adversity and stress in shaping and modifying our microbiome towards health and disease. The review shows that many factors such as the mode of delivery, breast milk, stress, diet and medications can greatly influence the development of our gut microbiome and potentially make us more prone to certain diseases. By incorporating environmental factors into models that study the microbiome in the setting of health and disease, may provide a better understanding of disease and potentially new areas of treatment. To highlight this, we will additionally explore the role of the environment and the microbiome in the development of obesity and functional bowel disorders.

Alterations in the brain-gut system have been implicated in various disease states, but little is known about how early-life adversity (ELA) impacts development and adult health as mediated by brain-gut interactions. We hypothesize that ELA disrupts components of the brain-gut system, thereby increasing susceptibility to disordered mood. In a sample of 128 healthy adult participants, a history of ELA and current stress, depression, and anxiety were assessed using validated questionnaires. Fecal metabolites were measured using liquid chromatography tandem mass spectrometry-based untargeted metabolomic profiling. Functional brain connectivity was evaluated by magnetic resonance imaging. Sparse partial least squares-discriminant analysis, controlling for sex, body mass index, age, and diet was used to predict brain-gut alterations as a function of ELA. ELA was correlated with four gut-regulated metabolites within the glutamate pathway (5-oxoproline, malate, urate, and glutamate gamma methyl ester) and alterations in functional brain connectivity within primarily sensorimotor, salience, and central executive networks. Integrated analyses revealed significant associations between these metabolites, functional brain connectivity, and scores for perceived stress, anxiety, and depression. This study reveals a novel association between a history of ELA, alterations in the brain-gut axis, and increased vulnerability to negative mood and stress. Results from the study raise the hypothesis that select gut-regulated metabolites may contribute to the adverse effects of critical period stress on neural development via pathways related to glutamatergic excitotoxicity and oxidative stress.

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The presence of advanced fibrosis is an important measure of the severity of chronic liver disease. Prior works that have examined the gut microbiome as a novel biomarker for advanced fibrosis have only examined patients with nonalcoholic fatty liver disease. Therefore, our goal was to examine the gut microbiome across varying etiologies of liver disease to create a predictive model for liver fibrosis based upon a microbial signature. Stool samples were obtained from patients with chronic liver disease (n = 50) undergoing FibroScan (ultrasound elastography) at the VA Greater Los Angeles Healthcare System. Healthy control patients (n = 25) were also recruited as a reference population. Fecal samples underwent 16S ribosomal RNA sequencing. Using differentially abundant microbes, a random forest classifier model was created to distinguish advanced fibrosis from mild/moderate fibrosis. The findings were then validated in a separate cohort of chronic liver disease patients (n = 37). Etiologies for liver disease included non-alcoholic liver disease (58.0%), hepatitis C (26.0%), hepatitis B (10.0%), and alcohol (6.0%). Microbiome composition was distinct in liver patients with advanced fibrosis compared to those with minimal fibrosis and healthy controls (p = 0.003). In multivariate negative binomial modeling, 26 bacterial taxa were differentially abundant in patients with advanced fibrosis as compared to those with minimal/moderate fibrosis (q-value < 0.05). A random forests classifier based on these taxa had an AUROC of 0.90 to predict advanced fibrosis. Prevotella copri, which was enriched in patients with advanced fibrosis, was the most strongly predictive microbe in the classifier. The classifier had an AUROC of 0.82 for advanced fibrosis in the validation cohort and Prevotella copri remained the strongest predictive microbe for advanced fibrosis. There is a distinct microbial signature for patients with advanced fibrosis independent of liver disease etiology and other comorbidities. These results suggest that microbial profiles can be used as a non-invasive marker for advanced fibrosis and support the hypothesis that microbes and their metabolites contribute to hepatic fibrosis.

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Background: Alterations in brain-gut-microbiome interactions have been implicated as an important factor in obesity. This study aimed to explore the relationship between food addiction (FA) and the brain-gutmicrobiome axis, using a multi-omics approach involving microbiome data, metabolomics, and brain imaging. Methods: Brain magnetic resonance imaging was obtained in 105 females. FA was defined by using the Yale Food Addiction Scale. Fecal samples were collected for sequencing and metabolomics. Statistical analysis was done by using multivariate analyses and machine learning algorithms. Results: Of the females with obesity, 33.3% exhibited FA as compared with 5.3% and 0.0% of females with overweight and normal BMI, respectively (P = 0.0001). Based on a multilevel sparse partial least square discriminant analysis, there was a difference in the gut microbiome of females with FA versus those without. Differential abundance testing showed Bacteroides, Megamonas, Eubacterium, and Akkermansia were statistically associated with FA (q < 0.05). Metabolomics showed that indolepropionic acid was inversely correlated with FA. FA was also correlated with increased connectivity within the brain's reward network, specifically between the intraparietal sulcus, brain stem, and putamen. Conclusions: This is the first study to examine FA along the braingut-microbiome axis and it supports the idea of targeting the braingut-microbiome axis for the treatment of FA and obesity.

Long-term use of rifaximin is associated with a decrease incidence of AKI and HRS and a decrease risk of requiring RRT in a general population of cirrhotic patients.