Project description:Lean nonalcoholic fatty liver disease (NAFLD) is increasingly recognized as a distinct clinical phenotype with limited evidence for effective non-pharmacological interventions and unclear mechanistic pathways. Aerobic exercise is recommended for NAFLD management; however, its effects and the gut microbiota–associated mechanisms in lean NAFLD remain incompletely understood. This dataset was generated from a randomized controlled trial (ClinicalTrials.gov identifier: NCT04882644). Participants assigned to the aerobic exercise intervention group provided fecal samples at baseline and after the 3-month intervention. A total of 33 paired fecal samples were included in this dataset. Gut microbiota profiles were generated using shotgun metagenomic sequencing. The dataset includes processed and de-identified species-level relative abundance tables derived from fecal samples collected before and after the intervention. These data were used to characterize exercise-induced alterations in gut microbial composition and interindividual variability in microbiota responses to aerobic exercise in lean NAFLD. The data support integrative analyses with clinical phenotypes and circulating metabolomic profiles to explore gut microbiota–associated mechanisms underlying the metabolic benefits of aerobic exercise.
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.
