Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively Combination of these methods enabled the reconstruction of the complete genome sequence of M oxyfera from the metagenome and identification of the functionally relevant enzymes and genes
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:Here we report metagenomic sequencing data in gut microbiota of autism spectrum disorders (ASD) compared with healthy volunteers (30 for ASD children and 30 for healthy controls, respectively). The genes changed in autistic subjects involved 1,312,364 analytes that compare to 1,335,835 analytes in healthy controls. The number of taxa in autistic subjects were significantly increased as compared to the healthy controls based on the phylum and genus level (P = 0.001). However, the number of species were significantly decreased in autistic subjects (P = 0.001).
Project description:Maternal obesity impacts neonatal outcomes; however, its influence on fetal gene expression and early gut microbiota composition remains insufficiently characterized. This prospective study was conducted in 62 full-term neonates between 2022 and 2024, analyzing transcriptomic profiles from umbilical-cord blood and metagenomic sequencing of fecal samples at 4 months. The cohort included 31 neonates born to mothers with normal BMI (NBMI) and 31 neonates born to mothers with overweight or obesity (OBMI). Major congenital anomalies, maternal exposure to drugs or antibiotics were exclusion criteria. OBMI neonates demonstrated significant upregulation of genes related to inflammation (MPO, OLR1) and cell-cycle dysregulation (GADD45G, CCNA1). Evidence of altered lysosomal function was observed, with increased expression of CTSG and CLTCL1 and reduced expression of HYAL1. Microbiome analysis revealed a decrease in Bacteroidota and an increase in Proteobacteria in cesarean-delivered neonates. Holdemanella was enriched in vaginally delivered OBMI neonates, suggesting a potential adaptive microbial response. Enrichment of opportunistic pathogens, including Klebsiella, Morganella, and Enterococcus, was observed in cesarean-delivered neonates, indicating a combined effect of maternal obesity and delivery mode on early microbial colonization. These findings suggest that maternal obesity modifies neonatal immune and metabolic gene expression while reshaping gut microbiome composition, with potential implications for long-term health.
Project description:Here we exploited a Han Chinese population-based cohort with extensive host metadata established in the Pinggu (PG) district of Beijing, and investigated gut microbiota from 2,338 adults (26-76 years) by metagenomic sequencing, revealing associations of the gut microbiota with sex, sex hormones, age, and a number of clinical and metabolic parameters.
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:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups