Ontology highlight
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PROVIDER: PRJNA1024543 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A comparision of soil microbial functional genes of three types of subtropical broad-leaved forests Microbial functional structure was significantly different among SBFs (P < 0.05). Compared to the DBF and the EBF, the MBF had higher alpha-diversity of functional genes but lower beta-diversity, and showed more complex functional gene networks.
2021-01-29 | GSE165723 | GEO
Project description:Genome scale metabolic model of Drosophila gut microbe Acetobacter fabarum
Abstract -
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
2021-07-01 | MODEL2002040002 | BioModels
Project description:Recent advances in (meta)genomic methods have provided new opportunities to examine host-microbe-environment interactions in the human gut. While opportunities exist to extract DNA from freshly sourced colonic tissue there are potentially valuable sources of DNA from historical studies that might also be examined. We examined how four different tissue DNA extraction methods employed in past clinical trials might impact the recovery of microbial DNA from a colonic tissue sample as assessed using a custom designed phylogenetic microarray for human gut bacteria and archaebacteria. While all methods of DNA extraction produced similar phylogenetic profiles some extraction specific biases were also observed. Real time PCR analysis targeting several bacterial groups substantiated this observation. These data suggest that while the efficacy of different DNA extraction methods differs somewhat all the methods tested produce an accurate representation of microbial diversity. This suggests that DNA samples archived in biobanks should be suitable for retrospective analyses. Three technical replicates per sample (extraction method) were analysed
2010-05-16 | E-GEOD-18420 | biostudies-arrayexpress
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
2013-10-30 | GSE51592 | GEO
Project description:To effectively monitor microbial populations in acidic environments and bioleaching systems, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the known genes associated with the acidophiles. This array contained 1,072 probes in which there were 571 related to 16S rRNA and 501 related to functional genes. Acid mine drainage (AMD) presents numerous problems to the aquatic life and surrounding ecosystems. However, little is known about the geographic distribution, diversity, composition, structure and function of AMD microbial communities. In this study, we analyzed the geographic distribution of AMD microbial communities from twenty sites using restriction fragment length polymorphism (RFLP) analysis of 16S rRNA genes, and the results showed that AMD microbial communities were geographically distributed and had high variations among different sites. Then an AMD-specific microarray was used to further analyze nine AMD microbial communities, and showed that those nine AMD microbial communities had high variations measured by the number of detected genes, overlapping genes between samples, unique genes, and diversity indices. Statistical analyses indicated that the concentrations of Fe, S, Ca, Mg, Zn, Cu and pH had strong impacts on both phylogenetic and functional diversity, composition, and structure of AMD microbial communities. This study provides insights into our understanding of the geographic distribution, diversity, composition, structure and functional potential of AMD microbial communities and key environmental factors shaping them. This study investigated the geographic distribution of Acid Mine Drainages microbial communities using a 16S rRNA gene-based RFLP method and the diversity, composition and structure of AMD microbial communities phylogenetically and functionally using an AMD-specific microarray which contained 1,072 probes ( 571 related to 16S rRNA and 501 related to functional genes). The functional genes in the microarray were involved in carbon metabolism (158), nitrogen metabolism (72), sulfur metabolism (39), iron metabolism (68), DNA replication and repair (97), metal-resistance (27), membrane-relate gene (16), transposon (13) and IST sequence (11).
2011-03-08 | E-GEOD-27542 | biostudies-arrayexpress
Project description:Extracellular vesicles (EVs) are released by most cell types and are implicated in several biological and pathological processes, including multiple sclerosis (MS). In this study we performed RNA sequencing to analyze the diversity of microorganisms by assignment of reads using different taxa profilers. To diminish the risk of false positive biases derived from sample handling, we performed a similar analysis on EVs derived from known cultured bacterial species, as well as artificially-generated samples. Overall, we detect a range of microbial species in MS and healthy control (HC) samples, that are not detected in control samples, as well as species with differential abundance between MS and HC samples. These results reveal the relevance of putative communication of microbial species using EVs as a communication vector.
2024-05-07 | GSE255317 | GEO
Project description:Despite the global importance of forests, it is virtually unknown how their soil microbial communities adapt at the phylogenetic and functional level to long term metal pollution. Studying twelve sites located along two distinct gradients of metal pollution in Southern Poland revealed that both community composition (via MiSeq Illumina sequencing of 16S rRNA genes) and functional gene potential (using GeoChip 4.2) were highly similar across the gradients despite drastically diverging metal contamination levels. Metal pollution level significantly impacted microbial community structure (p = 0.037), but not bacterial taxon richness. Metal pollution altered the relative abundance of specific bacterial taxa, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes and Proteobacteria. Also, a group of metal resistance genes showed significant correlations with metal concentrations in soil, although no clear impact of metal pollution levels on overall functional diversity and structure of microbial communities was observed. While screens of phylogenetic marker genes, such as 16S rRNA, provided only limited insight into resilience mechanisms, analysis of specific functional genes, e.g. involved in metal resistance, appeared to be a more promising strategy. This study showed that the effect of metal pollution on soil microbial communities was not straightforward, but could be filtered out from natural variation and habitat factors by multivariate statistical analysis and spatial sampling involving separate pollution gradients.
2014-07-22 | GSE59620 | GEO
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.
2018-04-16 | E-MTAB-5546 | biostudies-arrayexpress