Ontology highlight
ABSTRACT:
PROVIDER: PRJNA668920 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12832901_1.fastq.gz | Fastqsanger.gz | |||
| SRR12832901_2.fastq.gz | Fastqsanger.gz | |||
| SRR13933300_1.fastq.gz | Fastqsanger.gz | |||
| SRR13933300_2.fastq.gz | Fastqsanger.gz | |||
| SRR13933301_1.fastq.gz | Fastqsanger.gz |
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Project description:Metagenomic sequencing data of human gut microbiome
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Project description:Evaluation of short-read-only, long-read-only, and hybrid assembly approaches on metagenomic samples demonstrating how they affect gene and protein prediction which is relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic-based protein predictions.
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Project description:Distal gut bacteria play a pivotal role in the digestion of dietary polysaccharides by producing a large number of carbohydrate-active enzymes (CAZymes) that the host otherwise does not produce. We report here the design of a high density custom microarray that we used to spot non-redundant DNA probes for more than 6,500 genes encoding glycoside hydrolases and lyases selected from 174 reference genomes from distal gut bacteria. The custom microarray was tested and validated by the hybridization of bacterial DNA extracted from the stool samples of lean, obese and anorexic individuals. Our results suggest that a microarray-based study can detect genes from low-abundance bacteria better than metagenomic-based studies. A striking example was the finding that a gene encoding a GH6-family cellulase was present in all subjects examined, whereas metagenomic studies have consistently failed to detect this gene in both human and animal gut microbiomes. In addition, an examination of eight stool samples allowed the identification of a corresponding CAZome core containing 46 families of glycoside hydrolases and polysaccharide lyases, which suggests the functional stability of the gut microbiota despite large taxonomical variations between individuals.
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2019-11-09 | GSE140149 | GEO
Project description:The gut microbiome is significantly altered in inflammatory bowel diseases, but the basis of these changes is not well understood. We have combined metagenomic and metatranscriptomic profiling of the gut microbiome to assess changes to both bacterial community structure and transcriptional activity in a mouse model of colitis. Gene families involved in microbial resistance to oxidative stress, including Dps/ferritin, Fe-dependent peroxidase and glutathione S-transferase, were transcriptionally up-regulated in colitis, implicating a role for increased oxygen tension in gut microbiota modulation. Transcriptional profiling of the host gut tissue and host RNA in the gut lumen revealed a marked increase in the transcription of genes with an activated macrophage and granulocyte signature, suggesting the involvement of these cell types in influencing microbial gene expression. Down-regulation of host glycosylation genes further supports a role for inflammation-driven changes to the gut niche that may impact the microbiome. We propose that members of the bacterial community react to inflammation-associated increased oxygen tension by inducing genes involved in oxidative stress resistance. Furthermore, correlated transcriptional responses between host glycosylation and bacterial glycan utilisation support a role for altered usage of host-derived carbohydrates in colitis. Complementary transcription profiling data from the mouse hosts have also been deposited at ArrayExpress under accession number E-MTAB-3590 ( http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3590/ ).
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Project description:Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics (the study of the whole protein complement of a microbial community) can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification. Here we present a systematic investigation of variables concerning database construction and annotation, and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. Taxonomic and functional results were revealed to be strongly database-dependent, especially when dealing with mouse samples. As a striking example, in mouse the Firmicutes/Bacteroidetes ratio varied up to 10-fold depending on the database used. Finally, we provide recommendations regarding metagenomic sequence processing aimed at maximizing gut metaproteome characterization, and contribute to identify an optimized pipeline for metaproteomic data analysis.
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Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humans’ age. Metagenomic DNA from fecal samples of 123 healthy volunteers of four different age groups, i.e. pre-school Children (CH), School Children (SC), High School Students (HSS) and Adults (AD) were used for hybridization. The results showed that 80 different gene types were recovered from the 123 individuals gut microbiota, among which 25 were present in CH, 37 in SC, 58 in HSS and 72 in AD. Further analysis indicated that antibiotic resistance genes in groups of CH, SC and AD can be independently clustered, and those ones in group HSS are more divergent. The detailed analysis of antibiotic resistance genes in human gut is further described in the paper DNA microarray analysis reveals the antibiotic resistance gene diversity in human gut microbiota is age-related submitted to Sentific Reports
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