Project description:In this study, we performed a comparative analysis of gut microbiota composition and gut microbiome-derived bacterial extracellular vesicles (bEVs) isolated from patients with solid tumours and healthy controls. After isolating bEVs from the faeces of solid tumour patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of faeces from patientsand controls using 16S rRNA sequencing. Machine learning was used to classify the samples into patients and controls based on their bEVs and faecal microbiomes.
Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
Project description:Most proteogenomic approaches for mapping single amino acid polymorphisms (SAPs) require construction of a sample-specific database containing protein variants predicted from the next-generation sequencing (NGS) data. We present a new strategy for direct SAP detection without relying on NGS data. Among the 348 putative SAP peptides identified in an industrial yeast strain, 85.6% of SAP sites were validated by genomic sequencing.
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
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis
Project description:Opioids such as morphine have many beneficial properties as analgesics, however, opioids may induce multiple adverse gastrointestinal symptoms. We have recently demonstrated that morphine treatment results in significant disruption in gut barrier function leading to increased translocation of gut commensal bacteria. However, it is unclear how opioids modulate the gut homeostasis. By using a mouse model of morphine treatment, we studied effects of morphine treatment on gut microbiome. We characterized phylogenetic profiles of gut microbes, and found a significant shift in the gut microbiome and increase of pathogenic bacteria following morphine treatment when compared to placebo. In the present study, wild type mice (C57BL/6J) were implanted with placebo, morphine pellets subcutaneously. Fecal matter were taken for bacterial 16s rDNA sequencing analysis at day 3 post treatment. A scatter plot based on an unweighted UniFrac distance matrics obtained from the sequences at OTU level with 97% similarity showed a distinct clustering of the community composition between the morphine and placebo treated groups. By using the chao1 index to evaluate alpha diversity (that is diversity within a group) and using unweighted UniFrac distance to evaluate beta diversity (that is diversity between groups, comparing microbial community based on compositional structures), we found that morphine treatment results in a significant decrease in alpha diversity and shift in fecal microbiome at day 3 post treatment compared to placebo treatment. Taxonomical analysis showed that morphine treatment results in a significant increase of potential pathogenic bacteria. Our study shed light on effects of morphine on the gut microbiome, and its role in the gut homeostasis.