Environmental metagenomic samples
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA945605 | ENA |
REPOSITORIES: ENA
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Project description:The neurotoxic effects and mechanisms of low-dose and long-term sulfamethoxazole (SMZ) exposure remain unknown. This study exposed zebrafish to environmental SMZ concentrations and observed behavioral outcomes. SMZ exposure increased hyperactivity and altered the transcript levels of 17 genes associated with neurological function. It impaired intestinal function by reducing the number of intestinal goblet cells and lipid content. Metabolomic results indicated that the contents of several lipids and amino acids in the gut were altered, which might affect the expression levels of neurological function-related genes. Metagenomic results demonstrated that SMZ exposure substantially altered the composition of the gut microbiome. Zebrafish receiving a transplanted fecal microbiome from the SMZ group were also found to exhibit abnormal behavior, suggesting that the gut microbiome is an important target for SMZ exposure-induced neurobehavioral abnormalities. Multi-omics correlation analysis revealed that gut micrometabolic function was related to differential gut metabolite levels, which may affect neurological function through the gut-brain-axis. Reduced abundance of Lefsonia and Microbacterium was strongly correlated with intestinal metabolic function and may be the key bacterial genera in neurobehavioral changes. This study confirms for the first time that SMZ-induced neurotoxicity in zebrafish is closely mediated by alterations in the gut microbiome.
2024-02-22 | GSE255986 | GEO
Project description:Mammalian species have co-evolved with intestinal microbial communities that can shape development and adapt to environmental changes, including antibiotic perturbation or nutrient flux. In humans, especially children, microbiota disruption is common, yet the dynamic microbiome recovery from early-life antibiotics is still uncharacterized. Using a mouse model mimicking pediatric antibiotic use, we found that therapeutic-dose pulsed antibiotic treatment (PAT) with a beta-lactam or macrolide altered both host and microbiota development. Early-life PAT accelerated total mass and bone growth, and resulted in progressive changes in gut microbiome diversity, population structure, and metagenomic content, with microbiome effects dependent on the number of courses and class of antibiotic. While control microbiota rapidly adapted to a change in diet, PAT slowed the ecological progression, with delays lasting several months in response to the macrolide. This study identifies key markers of disturbance and recovery, which may help provide therapeutic targets for microbiota restoration following antibiotic treatment. C57BL/6J mice received three antibiotic courses: at days 10-15, 28-31, and 37-40 of life, amoxicillin or tylosin.Livers were collected at age 22 weeks, RNA was extracted, and transcriptional differences were measured by microarray analysis.
2015-05-07 | E-GEOD-68603 | biostudies-arrayexpress
Project description:Mammalian species have co-evolved with intestinal microbial communities that can shape development and adapt to environmental changes, including antibiotic perturbation or nutrient flux. In humans, especially children, microbiota disruption is common, yet the dynamic microbiome recovery from early-life antibiotics is still uncharacterized. Using a mouse model mimicking pediatric antibiotic use, we found that therapeutic-dose pulsed antibiotic treatment (PAT) with a beta-lactam or macrolide altered both host and microbiota development. Early-life PAT accelerated total mass and bone growth, and resulted in progressive changes in gut microbiome diversity, population structure, and metagenomic content, with microbiome effects dependent on the number of courses and class of antibiotic. While control microbiota rapidly adapted to a change in diet, PAT slowed the ecological progression, with delays lasting several months in response to the macrolide. This study identifies key markers of disturbance and recovery, which may help provide therapeutic targets for microbiota restoration following antibiotic treatment.
2015-05-07 | GSE68603 | GEO
Project description:Here we describe the application of metagenomic technologies to construct cDNA libraries from RNA isolated from environmental samples. RNAlater (Ambion) was shown to stabilize RNA in environmental samples for periods of at least 3 months at -20 degrees C. Protocols for library construction were established on total RNA extracted from Acanthamoeba polyphaga trophozoites. The methodology was then used on algal mats from geothermal hot springs in Tengchong county, Yunnan Province, People's Republic of China, and activated sludge from a sewage treatment plant in Leicestershire, United Kingdom. The Tenchong libraries were dominated by RNA from prokaryotes, reflecting the mainly prokaryote microbial composition. The majority of these clones resulted from rRNA; only a few appeared to be derived from mRNA. In contrast, many clones from the activated sludge library had significant similarity to eukaryote mRNA-encoded protein sequences. A library was also made using polyadenylated RNA isolated from total RNA from activated sludge; many more clones in this library were related to eukaryotic mRNA sequences and proteins. Open reading frames (ORFs) up to 378 amino acids in size could be identified. Some resembled known proteins over their full length, e.g., 36% match to cystatin, 49% match to ribosomal protein L32, 63% match to ribosomal protein S16, 70% to CPC2 protein. The methodology described here permits the polyadenylated transcriptome to be isolated from environmental samples with no knowledge of the identity of the microorganisms in the sample or the necessity to culture them. It has many uses, including the identification of novel eukaryotic ORFs encoding proteins and enzymes.
| S-EPMC1352286 | biostudies-literature
Project description:A major goal of metagenomics is to identify and study the entire collection of microbial species in a set of targeted samples. We describe a statistical metagenomic algorithm that simultaneously identifies microbial species and estimates their abundances without using reference genomes. As a trade-off, we require multiple metagenomic samples, usually ≥10 samples, to get highly accurate binning results. Compared to reference-free methods based primarily on k-mer distributions or coverage information, the proposed approach achieves a higher species binning accuracy and is particularly powerful when sequencing coverage is low. We demonstrated the performance of this new method through both simulation and real metagenomic studies. The MetaGen software is available at https://github.com/BioAlgs/MetaGen .
| S-EPMC5627425 | biostudies-other
Project description:In this study, the development and assessment of a modified, efficient, and cost-efficient protocol for mDNA (metagenomic DNA) extraction from contaminated water samples was attempted. The efficiency of the developed protocol was investigated in comparison to a well-established commercial kit (Epicentre, Metagenomic DNA Isolation Kit for Water). The comparison was in terms of degree of shearing, yield, purity, duration, suitability for polymerase chain reaction and next-generation sequencing in addition to the quality of next-generation sequencing data. The DNA yield obtained from the developed protocol was 2.6 folds higher than that of the commercial kit. No significant difference in the alpha (Observed species, Chao1, Simpson and PD whole tree) and beta diversity was found between the DNA samples extracted by the commercial kit and the developed protocol. The number of high-quality sequences of the samples extracted by the developed method was 20% higher than those obtained by the samples processed by the kit. The developed economic protocol successfully yielded high-quality pure mDNA compatible with complex molecular applications. Thus we propose the developed protocol as a gold standard for future metagenomic studies investigating a large number of samples.
| S-EPMC6328898 | biostudies-literature
Project description:environmental samples Raw sequence reads
| PRJNA498557 | ENA
Project description:Environmental samples Raw sequence reads
| PRJNA876961 | ENA