Ontology highlight
ABSTRACT:
PROVIDER: PRJNA826326 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18746800_1.fastq.gz | Fastqsanger.gz | |||
| SRR18746800_2.fastq.gz | Fastqsanger.gz | |||
| SRR18746801_1.fastq.gz | Fastqsanger.gz | |||
| SRR18746801_2.fastq.gz | Fastqsanger.gz | |||
| SRR18746802_1.fastq.gz | Fastqsanger.gz |
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Project description:Global studies of microbial diversity in pig gut
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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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Project description:The mammalian gut harbors a diverse microbial community (gut microbiota) that mainly consists of bacteria. Their combined genomes (the microbiome) provide biochemical and metabolic functions that complement host physiology. Maintaining symbiosis seems to be a key requirement for health as dysbiosis is associated with the development of common diseases. Previous studies indicated that the microbiota and the hostM-bM-^@M-^Ys epithelium signal bidirectional inducing transcriptional responses to fine-tune and maintain symbiosis. However, little is known about the hostM-bM-^@M-^Ys responses to the microbiota along the length of the gut as earlier studies of gut microbial ecology mostly used either colonic or fecal samples. This is of importance as not only function and architecture of the gut varies along its length but also microbial distribution and diversity. Few recent studies have begun to investigate microbiota-induced host responses along the length of the gut. However, these reports used whole tissue samples and therefore do not allow drawing conclusions about specificity of the observed responses. Which cells in the intestinal tissue are responsible for the microbially induced response: epithelial, mesenchymal or immune cells? Where are the responding cells located? We used using extensive microarray analysis of laser capture microdissection (LCM) harvested ileal and colonic tip and crypt fractions from germ-free and conventionally-raised mice to investigate the microbiota-induced transcriptional responses in specific and well-defined cell populations of the hostM-bM-^@M-^Ys epithelium. Ileum and colon segments were dissected from germ-free and conventionally-raised 10-12 weeks old female C57Bl/6 mice, washed and frozen as OCT blocks. Cryosections were prepared from these OCT blocks and tip/crypt fractions isolated using laser capture microdissection. To investigate the microbiota-induced transcriptional responses specific for specific subpopulations of intestinal epithelial cells, tip and crypt fractions of ileal and colonic epithelium of germ-free and conventionally-raised 10-12 weeks old female C57Bl/6 mice were harvested using laser capture microdissection and probed in an extensive microarray analysis.
2015-02-12 | E-GEOD-51910 | biostudies-arrayexpress
Project description:Recent advances in (meta)genomic methods have provided new opportunities to examine host-microbe-environment interactions in the human gut. While opportunities exist to extract DNA from freshly sourced colonic tissue there are potentially valuable sources of DNA from historical studies that might also be examined. We examined how four different tissue DNA extraction methods employed in past clinical trials might impact the recovery of microbial DNA from a colonic tissue sample as assessed using a custom designed phylogenetic microarray for human gut bacteria and archaebacteria. While all methods of DNA extraction produced similar phylogenetic profiles some extraction specific biases were also observed. Real time PCR analysis targeting several bacterial groups substantiated this observation. These data suggest that while the efficacy of different DNA extraction methods differs somewhat all the methods tested produce an accurate representation of microbial diversity. This suggests that DNA samples archived in biobanks should be suitable for retrospective analyses. Three technical replicates per sample (extraction method) were analysed
2010-05-16 | E-GEOD-18420 | biostudies-arrayexpress
Project description:global studies of microbial diversity on soil
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