Ontology highlight
ABSTRACT:
PROVIDER: PRJNA736854 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pathogen detection microarrays analyzing honeybee samples taken after parasitization with a predatory fly, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package.
2012-08-01 | GSE29749 | GEO
Project description:Aquatic microorganisms are typically identified as either oligotrophic or copiotrophic, representing trophic strategies adapted to low or high nutrient concentrations, respectively. Here, we sought to take steps towards identifying these and additional adaptations to nutrient availability with a quantitative analysis of microbial resource use in mixed communities. We incubated an estuarine microbial community with stable isotope labeled amino acids (AAs) at concentrations spanning three orders of magnitude, followed by taxon-specific quantitation of isotopic incorporation using NanoSIMS analysis of high-density microarrays. The resulting data revealed that trophic response to AA availability falls along a continuum between copiotrophy and oligotrophy, and high and low activity. To illustrate strategies along this continuum more simply, we statistically categorized microbial taxa among three trophic types, based on their incorporation responses to increasing resource concentration. The data indicated that taxa with copiotrophic-like resource use were not necessarily the most active, and taxa with oligotrophic-like resource use were not always the least active. Two of the trophic strategies were not randomly distributed throughout a 16S rDNA phylogeny, suggesting they are under selective pressure in this ecosystem and that a link exists between evolutionary relatedness and substrate affinity. The diversity of strategies to adapt to differences in resource availability highlights the need to expand our understanding of microbial interactions with organic matter in order to better predict microbial responses to a changing environment. manuscript accepted by PLoS ONE 4 datasets: 1) fluorescence data for 3 treatments combined, 2) isotopic data for treatment = LOW, 3) isotopic data for treatment = MEDIUM, 4) isotopic data for treatment = HIGH
2014-03-26 | E-GEOD-56119 | biostudies-arrayexpress
Project description:Aquatic microorganisms are typically identified as either oligotrophic or copiotrophic, representing trophic strategies adapted to low or high nutrient concentrations, respectively. Here, we sought to take steps towards identifying these and additional adaptations to nutrient availability with a quantitative analysis of microbial resource use in mixed communities. We incubated an estuarine microbial community with stable isotope labeled amino acids (AAs) at concentrations spanning three orders of magnitude, followed by taxon-specific quantitation of isotopic incorporation using NanoSIMS analysis of high-density microarrays. The resulting data revealed that trophic response to AA availability falls along a continuum between copiotrophy and oligotrophy, and high and low activity. To illustrate strategies along this continuum more simply, we statistically categorized microbial taxa among three trophic types, based on their incorporation responses to increasing resource concentration. The data indicated that taxa with copiotrophic-like resource use were not necessarily the most active, and taxa with oligotrophic-like resource use were not always the least active. Two of the trophic strategies were not randomly distributed throughout a 16S rDNA phylogeny, suggesting they are under selective pressure in this ecosystem and that a link exists between evolutionary relatedness and substrate affinity. The diversity of strategies to adapt to differences in resource availability highlights the need to expand our understanding of microbial interactions with organic matter in order to better predict microbial responses to a changing environment. manuscript accepted by PLoS ONE
2014-03-26 | GSE56119 | GEO
Project description:Pathogen detection microarrays analyzing honeybee samples taken after parasitization with a predatory fly, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package. Honey bees parasitized with the phorid fly Apocephalus borealis were screened for viral and non-viral pathogens by microarray.
2012-07-31 | E-GEOD-29749 | biostudies-arrayexpress
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