Project description:To investigate the TVA diet's effect on mouse gut microbiome, we fed C57/BL6 mice with TVA diet or CON diet for 18 days We then collected feces of the mice and performed 16S ribosomal RNA (rRNA) sequencing.
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.
Project description:Age-dependent changes of the gut-associated microbiome have been linked to increased frailty and systemic inflammation. This study found that age-associated changes of the gut microbiome of BALB/c and C57BL/6 mice could be reverted by co-housing of aged (22 months old) and adult (3 months old) mice for 30-40 days or faecal microbiota transplantation (FMT) from adult into aged mice. This was demonstrated using high-throughput sequencing of the V3-V4 hypervariable region of bacterial 16S rRNA gene isolated from faecal pellets collected from 3-4 months old adult and 22-23 months old aged mice before and after co-housing or FMT.
Project description:The human gut is colonized by trillions of microorganisms that influence human health and disease through the metabolism of xenobiotics, including therapeutic drugs and antibiotics. The diversity and metabolic potential of the human gut microbiome have been extensively characterized, but it remains unclear which microorganisms are active and which perturbations can influence this activity. Here, we use flow cytometry, 16S rRNA gene sequencing, and metatranscriptomics to demonstrate that the human gut contains distinctive subsets of active and damaged microorganisms, primarily composed of Firmicutes, which display marked temporal variation. Short-term exposure to a panel of xenobiotics resulted in significant changes in the physiology and gene expression of this active microbiome. Xenobiotic-responsive genes were found across multiple bacterial phyla, encoding novel candidate proteins for antibiotic resistance, drug metabolism, and stress response. These results demonstrate the power of moving beyond DNA-based measurements of microbial communities to better understand their physiology and metabolism. RNA-Seq analysis of the human gut microbiome during exposure to antibiotics and therapeutic drugs.
Project description:The gut microbiome plays an important role in normal immune function and has been implicated in several autoimmune disorders. Here we use high-throughput 16S rRNA sequencing to investigate the gut microbiome in subjects with multiple sclerosis (MS, n=61) and healthy controls (n=43). Alterations in the gut microbiome in MS include increases in the genera Methanobrevibacter and Akkermansia and decreases in Butyricimonas, and correlate with variations in the expression of genes involved in dendritic cell maturation, interferon signaling and NF-kB signaling pathways in circulating T cells and monocytes. Patients on disease-modifying treatment show increased abundances of the genera Prevotella and Sutterella, and decreased Sarcina, compared to untreated patients. MS patients of a second cohort show elevated breath methane compared to controls, consistent with our observation of increased gut Methanobrevibacter in MS in the first cohort. Further study is required to assess whether the observed alterations in the gut microbiome play a role in, or are a consequence of, MS pathogenesis.
Project description:Opioid analgesics are frequently prescribed in the United States and worldwide. However, serious side effects such as addiction, immunosuppression and gastrointestinal symptoms limit long term use. In the current study using a chronic morphine-murine model a longitudinal approach was undertaken to investigate the role of morphine modulation of gut microbiome as a mechanism contributing to the negative consequences associated with opioids use. The results revealed a significant shift in the gut microbiome and metabolome within 24 hours following morphine treatment when compared to placebo. Morphine induced gut microbial dysbiosis exhibited distinct characteristic signatures profiles including significant increase in communities associated with pathogenic function, decrease in communities associated with stress tolerance. Collectively, these results reveal opioids-induced distinct alteration of gut microbiome, may contribute to opioids-induced pathogenesis. Therapeutics directed at these targets may prolong the efficacy long term opioid use with fewer side effects.
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.