Ontology highlight
ABSTRACT:
PROVIDER: PRJNA532470 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8885840.fastq.gz | Fastqsanger.gz | |||
| SRR8885850.fastq.gz | Fastqsanger.gz | |||
| SRR8885860.fastq.gz | Fastqsanger.gz | |||
| SRR8885870.fastq.gz | Fastqsanger.gz | |||
| SRR8885831.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.
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