Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Chronic acid suppression by proton pump inhibitor (PPI) has been hypothesized to alter the gut microbiota via a change in intestinal pH. To evaluate the changes in gut microbiota composition by long-term PPI treatment. Twenty-four week old F344 rats were fed with (n = 5) or without (n = 6) lansoprazole (PPI) for 50 weeks. Then, profiles of luminal microbiota in the terminal ileum were analyzed. Pyrosequencing for 16S rRNA gene was performed by genome sequencer FLX (454 Life Sciences/Roche) and analyzed by metagenomic bioinformatics.
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
Project description:This SuperSeries is composed of the SubSeries listed below. We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria.
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This series includes gene expression of the laser microdissected compartments of the ileum such as villous epithelium, lamina propria and crypts from specific pathogen free mice common reference design with a pool of small intestine RNA labeled with Cy3
Project description:We analyzed the effects of antibiotics using a popular model of gut microbiota depletion in mice by a cocktail of antibiotics. We combined intestinal transcriptome together with metagenomic analysis of the gut microbiota to develop a new bioinformatics approach that probes the links between microbial components and host functions. We found that most antibiotic-induced alterations can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues; and the effects of remaining antibiotic-resistant microbes. While microbe depletion led to down-regulation of immunity, the two other factors primarily inhibited mitochondrial gene expression and amounts of active mitochondria, and induced cell death. By reconstructing and analyzing a transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria. This series includes gene expression in the ileum of control, antibiotics (ABx)-treated, germfree, germfree-ABx-treated and mice colonized with normal or Abx-resistant microbiota. common reference design with a pool of small intestine RNA labeled with Cy3