Human gut microbiota sequence
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA992102 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25179500_1.fastq.gz | Fastqsanger.gz | |||
| SRR25179500_2.fastq.gz | Fastqsanger.gz | |||
| SRR25179501_1.fastq.gz | Fastqsanger.gz | |||
| SRR25179501_2.fastq.gz | Fastqsanger.gz | |||
| SRR25179502_1.fastq.gz | Fastqsanger.gz |
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Project description:Human gut microbiota Raw sequence reads
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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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2014-01-16 | GSE54070 | GEO
Project description:We used a DNA microarray chip covering 369 resistance types to investigate the relation of antibiotic resistance gene diversity with humansM-bM-^@M-^Y 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 The antibiotic resistance gene microarray is custom-designed (Roche NimbleGen), based on a single chip containing 3 internal replicated probe sets of 12 probes per resistance gene, covering the whole 315K 12-plex platform spots.
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Project description:Gut microbiota dysbiosis characterizes systemic metabolic alteration, yet its causality is debated. To address this issue, we transplanted antibiotic-free conventional wild-type mice with either dysbiotic (“obese”) or eubiotic (“lean”) gut microbiota and fed them either a NC or a 72%HFD. We report that, on NC, obese gut microbiota transplantation reduces hepatic gluconeogenesis with decreased hepatic PEPCK activity, compared to non-transplanted mice. Of note, this phenotype is blunted in conventional NOD2KO mice. By contrast, lean microbiota transplantation did not affect hepatic gluconeogenesis. In addition, obese microbiota transplantation changed both gut microbiota and microbiome of recipient mice. Interestingly, hepatic gluconeogenesis, PEPCK and G6Pase activity were reduced even once mice transplanted with the obese gut microbiota were fed a 72%HFD, together with reduced fed glycaemia and adiposity compared to non-transplanted mice. Notably, changes in gut microbiota and microbiome induced by the transplantation were still detectable on 72%HFD. Finally, we report that obese gut microbiota transplantation may impact on hepatic metabolism and even prevent HFD-increased hepatic gluconeogenesis. Our findings may provide a new vision of gut microbiota dysbiosis, useful for a better understanding of the aetiology of metabolic diseases. all livers are from NC-fed mice only.
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