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:We used a metagenomic microarray to detect Human Pegivirus in serum and cerebrospinal fluid from a patient suffering from severe encephalitis.
Project description:We applied metagenomic shotgun sequencing to investigate the effects of ZEA exposure on the change of mouse gut microbiota composition and function.
Project description:Here we developed a new approach to sepsis diagnosis that integrates host transcriptional profiling with metagenomic broad-range pathogen detection from cell-free plasma RNA and DNA.
Project description:Here we developed a new approach to sepsis diagnosis that integrates host transcriptional profiling with metagenomic broad-range pathogen detection from cell-free plasma RNA and DNA.
Project description:To unravel distinct pattern of metagenomic surveillance and respiratory microbiota between Mycoplasma pneumoniae (M. pneumoniae) P1-1 and P1-2 and explore the impact of COVID-19 pandemic on epidemiological features
Project description:Interventions: Group 1: Surgical patients undergoing surgery for colorectal cancer: immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples perioperatively and during oncologic follow-up.
Group 2: oncologic patients with chemo- / immune therapy without recent surgery:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa and saliva samples during therapy and oncological follow-up.
Group 3: healthy controls:
Immunophenotyping by PBMCs and metagenomic analyses from stool, mucosa, and saliva samples at the time of screening colonoscopy.
Primary outcome(s): Difference in the differential abundance of the colonic mucosa of patients with CRC vs. healthy controls for evaluation as diagnostic biomarkers based on metagenomic analyzes (microbial pattern)
Study Design: Allocation: ; Masking: ; Control: ; Assignment: ; Study design purpose: diagnostic
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.
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.