Ontology highlight
ABSTRACT:
PROVIDER: PRJNA503310 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8143240_1.fastq.gz | Fastqsanger.gz | |||
| SRR8143240_2.fastq.gz | Fastqsanger.gz | |||
| SRR8143250_1.fastq.gz | Fastqsanger.gz | |||
| SRR8143250_2.fastq.gz | Fastqsanger.gz | |||
| SRR8143260_1.fastq.gz | Fastqsanger.gz |
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Project description:Opioids such as morphine have many beneficial properties as analgesics, however, opioids may induce multiple adverse gastrointestinal symptoms. We have recently demonstrated that morphine treatment results in significant disruption in gut barrier function leading to increased translocation of gut commensal bacteria. However, it is unclear how opioids modulate the gut homeostasis. By using a mouse model of morphine treatment, we studied effects of morphine treatment on gut microbiome. We characterized phylogenetic profiles of gut microbes, and found a significant shift in the gut microbiome and increase of pathogenic bacteria following morphine treatment when compared to placebo. In the present study, wild type mice (C57BL/6J) were implanted with placebo, morphine pellets subcutaneously. Fecal matter were taken for bacterial 16s rDNA sequencing analysis at day 3 post treatment. A scatter plot based on an unweighted UniFrac distance matrics obtained from the sequences at OTU level with 97% similarity showed a distinct clustering of the community composition between the morphine and placebo treated groups. By using the chao1 index to evaluate alpha diversity (that is diversity within a group) and using unweighted UniFrac distance to evaluate beta diversity (that is diversity between groups, comparing microbial community based on compositional structures), we found that morphine treatment results in a significant decrease in alpha diversity and shift in fecal microbiome at day 3 post treatment compared to placebo treatment. Taxonomical analysis showed that morphine treatment results in a significant increase of potential pathogenic bacteria. Our study shed light on effects of morphine on the gut microbiome, and its role in the gut homeostasis.
2018-04-16 | E-MTAB-5546 | biostudies-arrayexpress
Project description:Genome scale metabolic model of Drosophila gut microbe Acetobacter fabarum
Abstract -
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
2021-07-01 | MODEL2002040002 | BioModels
Project description:Morphine and its pharmacological derivatives are the most prescribed analgesics for moderate to severe pain management. However, chronic use of morphine reduces pathogen clearance and induces bacterial translocation across the gut barrier. The enteric microbiome has been shown to play a critical role in the preservation of the mucosal barrier function and metabolic homeostasis. Here, we show for the first time, using bacterial 16s rDNA sequencing, that chronic morphine treatment significantly alters the gut microbial composition and induces preferential expansion of the gram-positive pathogenic and reduction of bile-deconjugating bacterial strains. A significant reduction in both primary and secondary bile acid levels was seen in the gut, but not in the liver with morphine treatment. Morphine induced microbial dysbiosis and gut barrier disruption was rescued by transplanting placebo-treated microbiota into morphine-treated animals, indicating that microbiome modulation could be exploited as a therapeutic strategy for patients using morphine for pain management. In this study, we establish a link between the two phenomena, namely gut barrier compromise and dysregulated bile acid metabolism. We show for the first time that morphine fosters significant gut microbial dysbiosis and disrupts cholesterol/bile acid metabolism. Changes in the gut microbial composition is strongly correlated to disruption in host inflammatory homeostasis13,14 and in many diseases (e.g. cancer/HIV infection), persistent inflammation is known to aid and promote the progression of the primary morbidity. We show here that chronic morphine, gut microbial dysbiosis, disruption of cholesterol/bile acid metabolism and gut inflammation; have a linear correlation. This opens up the prospect of devising minimally invasive adjunct treatment strategies involving microbiome and bile acid modulation and thus bringing down morphine-mediated inflammation in the host.
2016-06-01 | E-MTAB-3722 | biostudies-arrayexpress
Project description:The microbial population that live within the gut of animals influences their physiology. We used axenic and recolonized flies to identify genes whose expression is modulated by the presence of a bacterial flora in the gut. We identified several up regulated genes, most of which are described as enriched in the midgut, and related either to immunity or to metabolism. This work also suggests that most microbiota regulated genes are Relish dependent.
2014-03-26 | GSE56173 | GEO
Project description:Background: Gastrointestinal symptoms in COVID-19 patients suggests that the gut may present a viral target organ. Disease development and severity is dependent on viral interaction with two cell surface human proteins, ACE2 and TMPRSS2, and on antiviral response which may lead to systemic hyperinflammatory syndrome and multiorgan dysfunction Understanding the host response to SARS-CoV-2 infection and the pathology of the disease will be greatly enhanced by the development of appropriate animal models. However, the virus does not grow in wild type mice and only induced mild disease in transgenic animals expressing human ACE2. Results: As there are known differences between immune response in laboratory mice and humans, the response of human gut developed as xenografts and host mouse gut following systemic LPS injections as a hyperinflammation model system was evaluated. Gene set enrichment analysis of significantly upregulated human and mouse genes revealed that a number of inflammatory and immune response pathways are commonly regulated in the two species. However, species differences were also observed. The analysis shows that the intestinal immune response to inflammation in humans and mice are generally very similar. However, certain human-specific diseases, such as COVID-19, can only be successfully studied in an experimental model of human tissue, such as the gut xenograft
2022-06-01 | GSE180795 | GEO
Project description:Accumulating evidence demonstrates that the gut microbiota affects brain function and behavior, including depressive behavior. Antidepressants are the main drugs used for treatment of depression. We hypothesized that antidepressant treatment could modify gut microbiota which can partially mediate their antidepressant effects. Mice were chronically treated with one of five antidepressants (fluoxetine, escitalopram, venlafaxine, duloxetine or desipramine), and gut microbiota was analyzed, using 16s rRNA gene sequencing. After characterization of differences in the microbiota, chosen bacterial species were supplemented to vehicle and antidepressant-treated mice, and depressive-like behavior was assessed to determine bacterial effects. RNA-seq analysis was performed to determine effects of bacterial treatment in the brain. Antidepressants reduced richness and increased beta diversity of gut bacteria, compared to controls. At the genus level, antidepressants reduced abundances of Ruminococcus, Adlercreutzia, and an unclassified Alphaproteobacteria. To examine implications of the dysregulated bacteria, we chose one of antidepressants (duloxetine) and investigated if its antidepressive effects can be attenuated by simultaneous treatment with Ruminococcus flavefaciens or Adlercreutzia equolifaciens. Supplementation with R. flavefaciens diminished duloxetine-induced decrease in depressive-like behavior, while A. equolifaciens had no such effect. R. flavefaciens treatment induced changes in cortical gene expression, up-regulating genes involved in mitochondrial oxidative phosphorylation, while down-regulating genes involved in neuronal plasticity. Our results demonstrate that various types of antidepressants alter gut microbiota composition, and further implicate a role for R. flavefaciens in alleviating depressive-like behavior.
2019-04-05 | GSE129359 | GEO
Project description:An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and its impact on host physiology. This research can be confounded by poorly-understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multi-way interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle including 2-oxoglutarate and succinate are produced at high flux and cross-fed between bacterial taxa suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.
2021-07-01 | MODEL2002040003 | BioModels
Project description:An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and its impact on host physiology. This research can be confounded by poorly-understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multi-way interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle including 2-oxoglutarate and succinate are produced at high flux and cross-fed between bacterial taxa suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.
2021-07-01 | MODEL2002040004 | BioModels
Project description:An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and its impact on host physiology. This research can be confounded by poorly-understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multi-way interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle including 2-oxoglutarate and succinate are produced at high flux and cross-fed between bacterial taxa suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.
2021-07-01 | MODEL2002040006 | BioModels