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:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
Project description:Significant gut microbiota heterogeneity exists amongst UC patients though the clinical implications of this variance are unknown. European and South Asian UC patients exhibit distinct disease risk alleles, many of which regulate immune function and relate to variation in gut microbiota β-diversity. We hypothesized ethnically distinct UC patients exhibit discrete gut microbiotas with unique luminal metabolic programming that influence adaptive immune responses and relate to clinical status. Using parallel bacterial 16S rRNA and fungal ITS2 sequencing of fecal samples (UC n=30; healthy n=13), we corroborated previous observations of UC-associated depletion of bacterial diversity and demonstrated significant gastrointestinal expansion of Saccharomycetales as a novel UC characteristic. We identified four distinct microbial community states (MCS 1-4), confirmed their existence using microbiota data from an independent UC cohort, and show they co-associate with patient ethnicity and degree of disease severity. Each MCS was predicted to be uniquely enriched for specific amino acid, carbohydrate, and lipid metabolism pathways and exhibited significant luminal enrichment of metabolic products from these pathways. Using a novel in vitro human DC/T-cell assay we show that DC exposure to patient fecal water led to MCS -specific changes in T-cell populations, particularly the Th1:Th2 ratio, and that patients with the most severe disease exhibited the greatest Th2 skewing. Thus, based on ethnicity, microbiome composition, and associated metabolic dysfunction, UC patients may be stratified in a clinically and immunologically meaningful manner, providing a platform for the development of FMC-focused therapy. Fecal microbiome was assessed with Affymetrix PhyloChip arrays from patients with ulcerative colitis and healthy controls.
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
Project description:Morphine causes microbial dysbiosis. In this study we focused on restoration of native microbiota in morphine treated mice and looked at the extent of restoration and immunological consequences of this restoration. Fecal transplant has been successfully used clinically, especially for treating C. difficile infection2528. With our expanding knowledge of the central role of microbiome in maintenance of host immune homeostasis17, fecal transplant is gaining importance as a therapy for indications resulting from microbial dysbiosis. There is a major difference between fecal transplant being used for the treatment of C. difficile infection and the conditions described in our studies. The former strategy is based on the argument that microbial dysbiosis caused by disproportionate overgrowth of a pathobiont can be out-competed by re-introducing the missing flora by way of a normal microbiome transplant. This strategy is independent of host factors and systemic effects on the microbial composition. Here, we show that microbial dysbiosis caused due to morphine can be reversed by transplantation of microbiota from the placebo-treated animals.
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).