Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: cDNA of Trypoxylus dichotomus gut bacteria

PROVIDER: PRJNA781626 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR17009212_1.fastq.gz	Fastqsanger.gz
	SRR17009212_2.fastq.gz	Fastqsanger.gz
	SRR17009213_1.fastq.gz	Fastqsanger.gz
	SRR17009213_2.fastq.gz	Fastqsanger.gz
	SRR17009214_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Project description:Trypoxylus dichotomus gut bacteria

| PRJNA781432 | ENA

Trypoxylus dichotomus

Project description:Trypoxylus dichotomus transcriptome

| PRJDB10443 | ENA

Trypoxylus dichotomus

Project description:Trypoxylus dichotomus overview

| PRJNA321076 | ENA

Trypoxylus dichotomus

Project description:Trypoxylus dichotomus larval horn transcriptome

| PRJDB6456 | ENA

The gut microbes of Trypoxylus dichotomus

Project description:The gut microbes of Trypoxylus dichotomus Raw sequence reads

| PRJNA1126440 | ENA

Trypoxylus dichotomus

Project description:Trypoxylus dichotomus Transcriptome or Gene expression

| PRJNA231720 | ENA

Trypoxylus dichotomus isolate:ZJPA

Project description:Trypoxylus dichotomus isolate:ZJPA Genome sequencing and assembly

| PRJNA688811 | ENA

Gut microbiota analysis after 3months probiotic-like bacteria or placebo treatment in subjects with metabolic syndrome

Project description:Background: Probiotic-like bacteria treatment has been described to be associated with gut microbiota modifications. Goal: To decipher if the effects of the tested probiotic-like bacteria are due to the bacteria itself or due to the effects of the bacteria on the gut microbiota. Methodology: In this study, gut microbiota has been analyzed from feces samples of subjects with metabolic syndrome and treated with one of the 2 tested probiotic-like bacteria or with the placebo during 3months.

| EGAS00001003585 | EGA

Morphine treatment induces distinct changes in the gut microbiome at day 3 post treatment

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

Comparative analysis of gut microbiota profile between young people and aged people

Project description:Given the criticle role of gut bacteria involve in number of diseases, the gut microbiota from young and aged people were estimated using 16s rRNA next-generation sequencing. This study will benefit to identify the role of gut bacteria on the pathegenic mechasim of aging relative diseases.

2022-07-20 | GSE165471 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data