Soil bacterial, fungal and animal community
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ABSTRACT:
PROVIDER: PRJNA613193 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:soil bacterial, fungal and animal community metagenome (GREAT SOILS project) Targeted loci environmental
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Project description:The effects of two years' winter warming on the overall fungal functional gene structure in Alaskan tundra soil were studies by the GeoChip 4.2 Resuts showed that two years' winter warming changed the overall fungal functional gene structure in Alaskan tundra soil.
2019-03-07 | GSE127899 | GEO
Project description:Identifying the genetic basis for natural selection is a fundamental research goal, and particularly significant for soil fungi because of their central role in ecosystem functioning. Here, we identify rapid evolutionary processes in the plant root colonizing insect pathogen Metarhizium robertsii. While adapting to a new soil community, expression of TATA box containing cell wall and stress response genes evolved at an accelerated rate, whereas virulence determinants, transposons and chromosome structure were unaltered. The survival of diversified field isolates was increased, confirming that the mutations were adaptive, and we further show that large populations of Metarhizium are principally maintained by associations with plant roots rather than insect populations. These results provide a mechanistic basis for understanding mutational and selective effects on soil microbes.
2012-01-04 | GSE30175 | GEO
Project description:Soil fungal community Raw sequence reads
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Project description:Soil fungal community Raw sequence reads
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Project description:Here we have compared adult wildtype (N2) C. elegans gene expression when grown on different bacterial environments/fod sources in an effort to model naturally occuring nematode-bacteria interactions at the Konza Prairie. We hypothesize that human-induced changes to natural environments, such as the addition of nitrogen fertalizer, have effects on the bacterial community in soils and this drives downstream changes in the structure on soil bacterial-feeding nematode community structure. Here we have used transcriptional profiling to identify candidate genes involved in the interaction of nematodes and bacteria in nature.
2009-05-02 | GSE15923 | GEO
Project description:The rate, timing, and mode of species dispersal is recognized as a key driver of the structure and function of communities of macroorganisms, and may be one ecological process that determines the diversity of microbiomes. Many previous studies have quantified the modes and mechanisms of bacterial motility using monocultures of a few model bacterial species. But most microbes live in multispecies microbial communities, where direct interactions between microbes may inhibit or facilitate dispersal through a number of physical (e.g., hydrodynamic) and biological (e.g., chemotaxis) mechanisms, which remain largely unexplored. Using cheese rinds as a model microbiome, we demonstrate that physical networks created by filamentous fungi can impact the extent of small-scale bacterial dispersal and can shape the composition of microbiomes. From the cheese rind of Saint Nectaire, we serendipitously observed the bacterium Serratia proteamaculans actively spreads on networks formed by the fungus Mucor. By experimentally recreating these pairwise interactions in the lab, we show that Serratia spreads on actively growing and previously established fungal networks. The extent of symbiotic dispersal is dependent on the fungal network: diffuse and fast-growing Mucor networks provide the greatest dispersal facilitation of the Serratia species, while dense and slow-growing Penicillium networks provide limited dispersal facilitation. Fungal-mediated dispersal occurs in closely related Serratia species isolated from other environments, suggesting that this bacterial-fungal interaction is widespread in nature. Both RNA-seq and transposon mutagenesis point to specific molecular mechanisms that play key roles in this bacterial-fungal interaction, including chitin utilization and flagellin biosynthesis. By manipulating the presence and type of fungal networks in multispecies communities, we provide the first evidence that fungal networks shape the composition of bacterial communities, with Mucor networks shifting experimental bacterial communities to complete dominance by motile Proteobacteria. Collectively, our work demonstrates that these strong biophysical interactions between bacterial and fungi can have community-level consequences and may be operating in many other microbiomes.
2017-08-02 | GSE85095 | GEO
Project description:Soil fungal community Raw sequence reads under GO
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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