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Ontology highlight
ABSTRACT:
PROVIDER: PRJEB51719 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR9289900_1.fastq.gz | Fastqsanger.gz | |||
| ERR9289900_2.fastq.gz | Fastqsanger.gz | |||
| ERR9289910_1.fastq.gz | Fastqsanger.gz | |||
| ERR9289910_2.fastq.gz | Fastqsanger.gz | |||
| ERR9289920_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 1926 |
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Project description:Insect gut microbiota plays important roles in acquiring nutrition, preventing pathogens infection, immune responses, and communicating with the environment. Gut microbiota can be affected by some external factors such as foods, temperature, and antibiotics. Spodoptera frugiperda (Lepidoptera: Noctuidae) is an important destructive pest of grain crops all over the world. The function of gut microbiota in S. frugiperda remains to be investigated. In this study, we fed the S. frugiperda with the antibiotic mixture (penicillin, gentamicin, rifampicin, and streptomycin) to perturb the gut microbiota, and further examined the effect of dysbiosis in gut microbiota on the gene expression of S. frugiperda by RNA sequencing. We found the composition and diversity of the gut bacterial community were changed in S. frugiperda after antibiotics treatmen, and the expression of genes related to energy and metabolic process were affected after antibiotics exposure in S. frugiperda. Our work will help understand the role of gut microbiota in insects.
2021-08-06 | GSE175476 | GEO
Project description:Microbiota assembly in the infant gut is influenced by time and duration of dietary exposure to breast-milk, infant formula and solid foods.
2023-10-18 | MSV000093140 | MassIVE
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-01-26 | E-GEOD-60568 | biostudies-arrayexpress
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This series includes gene expression in the ileum of control, antibiotics (ABx)-treated, germfree, germfree-ABx-treated and mice colonized with normal or Abx-resistant microbiota. common reference design with a pool of small intestine RNA labeled with Cy3
2015-01-26 | E-GEOD-60566 | biostudies-arrayexpress
Project description:Effects of current therapeutic foods in undernourished Bangladeshi children compared to microbiota-directed food prototypes in gnotobiotic mice and piglets
2018-04-18 | MSV000082286 | MassIVE
Project description:In vitro gut microbiota models are often used to study drug-microbiome interaction. Similar to culturing individual microbial strains, the biomass accumulation of in vitro gut microbiota follows a logistic growth curve. Current studies on in vitro gut microbiome responses introduce drug stimulation during different growth stages, e.g. lag phase or stationary phase. However, in vitro gut microbiota in different growth phases may respond differently to a same stimuli. Therefore, in this study, we used a 96-deep well plate-based culturing model (MiPro) to culture the human gut microbiota. Metformin, as the stimulus, was added at the lag, log and stationary phases of growth. Microbiome samples were collected at different time points for optical density and metaproteomic functional analysis. Results show that in vitro gut microbiota responded differently to metformin added during different growth phases, in terms of the growth curve, alterations of taxonomic and functional compositions. The addition of drugs at log phase leads to the greatest decline of bacterial growth. Metaproteomic analysis suggested that the strength of the metformin effect on the gut microbiome functional profile was ranked as lag phase > log phase > stationary phase. Our results showed that metformin added at lag phase resulted in a significantly reduced abundance of the Clostridiales order as well as an increased abundance of the Bacteroides genus, which was different from stimulation during the rest of the growth phase. Metformin also resulted in alterations of several pathways, including energy production and conversion, lipid transport and metabolism, translation, ribosomal structure and biogenesis. Our results indicate that the timing for drug stimulation should be considered when studying drug-microbiome interactions in vitro.
2022-03-01 | PXD017390 | Pride
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This series includes gene expression of the laser microdissected compartments of the ileum such as villous epithelium, lamina propria and crypts from specific pathogen free mice common reference design with a pool of small intestine RNA labeled with Cy3
2015-01-26 | E-GEOD-60567 | biostudies-arrayexpress
Project description:Introduction: Chronic sleep fragmentation (SF) is prevalent in contemporary human society, highlighting detrimental effects on glucose metabolism and adipose tissue morphology, which is closely linked to gut microbiota composition. However, it remains unclear whether sleep recovery (SR) after prolonged SF can ameliorate glucose metabolism, influence the transcriptome of inguinal white adipose tissue (iWAT), and whether these effects align with alterations in the gut microbiota. Methods: Mice were subjected to 8 weeks of SF and subsequently allowed 2 weeks of SR. We assessed glucose tolerance through intraperitoneal glucose tolerance tests (ipGTT), analyzed gut microbiota via 16s rDNA amplicon sequencing, and examined transcriptomic alterations in iWAT using RNA sequencing. Results: Despite the two-week SR following chronic SF, significant glucose intolerance persisted, accompanied by subtle shifts in the gut microbiota and alterations in gene expression within iWAT. The top hub genes Ncapg, Cenpe, and Tik were identified from the protein-protein interaction network. Conclusion: Even followed by a brief period of SR, prolonged SF still led to ongoing glucose intolerance and alterations in the adipose tissue transcriptome in mice. These changes were intertwined with modifications in the gut microbiome. The shifts in gut microbiota may play a pivotal role in understanding the sustained negative effects of SF.
2024-06-30 | GSE248189 | GEO
Project description:The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluoroxypyr, and ethoxyquin causing a substantial reduction (log2FC <-0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.
2024-02-21 | PXD047410 | Pride
Project description:<p>We investigate the hypothesis that consistent changes in the human gut microbiome are associated with Crohn's disease, a form of inflammatory bowel disease, and that altered microbiota contributes to pathogenesis. Analysis of this problem is greatly complicated by the fact that multiple factors influence the composition of the gut microbiota, including diet, host genotype, and disease state. For example, data from us and others document a drastic impact of diet on the composition of the gut microbiome. No amount of sequencing will yield a useful picture of the role of the microbiota in disease if samples are confounded with uncontrolled variables.</p> <p>We aim to characterize the composition of the gut microbiome while controlling for diet, host genotype, and disease state. Diet is controlled by analyzing children treated for Crohn's disease by placing them on a standardized elemental diet, and by testing effects of different diets on the gut microbiome composition in adult volunteers. Genotype is analyzed by large scale SNP genotyping, which is already underway and separately funded--team member Hakon Hakonarson is currently genotyping 50 children a week at ~half a million loci each and investigating connections with inflammatory bowel disease. Clinical status is ascertained in the very large IBD practice in the UPenn/CHOP hospital system. Effects of diet, host genotype, and disease state on the gut microbiome are summarized in a multivariate model, allowing connections between microbiome and disease to be assessed free of confounding factors.</p> <p>This project is divided into four sub-studies. In the Fecal Storage Methods (FSM) study, methods of stool storage and DNA extraction are compared to examine their impact on DNA sequence analysis results. The Controlled Feeding Experiment (CaFE) addresses the effects of controlled diets on the gut microbiome. In the Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO), the effects of diet analyzed using surveys and deep sequencing of stool specimens. The fourth study, Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE), examines the effects of an elemental diet treatment on pediatric patients diagnosed with inflammatory bowel disease (IBD), particularly Crohn's disease.</p> <p> <ul> <li>Fecal Storage Methods (FSM): Cross-sectional study</li> <li>Controlled Feeding Experiment (CaFE): Controlled trial</li> <li>Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO): Cross-sectional study</li> <li>Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE): Longitudinal cohort study</li> </ul> </p>
| phs000252 | dbGaP