Dataset Information

Bacteroides acidifaciens

ABSTRACT: Bacteroides acidifaciens Genome sequencing

PROVIDER: PRJNA1154812 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	SRR30544737_1.fastq.gz	Fastqsanger.gz
	SRR30544737_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 2 of 2

Similar Datasets

Project description:Background & Aims: Gut microbiota dysbiosis is associated with the pathogenesis of Crohn's disease (CD), but the underlying mechanisms by which colon bacteria contribute to the development of CD remain largely unclear. Here, we investigated whether colon bacteria, particularly Bacteroides acidifaciens (B. acidifaciens), promote CD pathogenesis through their small RNAs (sRNAs). Methods: The composition of gut bacteria were analyzed in the fecal samples of IL-10 knockout (KO) mice and CD45RBhigh mice that spontaneously develop colitis via 16S amplification sequencing, and the expression pattern of B. acidifaciens in both experimental colitis mice and CD patients was confirmed by quantitative RT-PCR (qRT-PCR). The effects of B. acidifaciens and their total and small RNA contents on colitis development were evaluated in IL-10 KO mice. Furthermore, the expression profile of B. acidifaciens-derived sRNA (BA-sRNA) in IL-10 KO mice was established by RNA sequencing, and BA-sRNA-172 levels in experimental colitis mice and CD patients were determined. Lentivirus carrying BA-sRNA-172 and BA-sRNA-172-deficient B. acidifaciens were then constructed and used to investigate the role of BA-sRNA-172 in the development of colitis. The activities of BA-sRNA-172 in regulating mucin2 (MUC2) expression and gut mucosal barrier function was systematically studied by in situ hybridization, immunofluorescence staining, qRT-PCR, western blot, RNA pull-down and luciferase assays in vitro. Finally, the effects of anti-BA-sRNA-172 and anti-MUC2 shRNA on intestinal barrier function and colitis development were evaluated. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

Dataset Information

Bacteroides acidifaciens

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets