Groundwater microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA865514 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:Pristine groundwater is a highly stable environment with microbes adapted to dark, oligotrophic conditions. Input events like heavy rainfalls can introduce excess particulate organic matter including surface-derived microbes into the groundwater, hereby creating a disturbance to the groundwater microbiome. Some of the translocated bacteria are not able to thrive in groundwater and will form necromass. Here, we investigated the effects of necromass addition to the microbial community in fractured bedrock groundwater, using groundwater mesocosms as model systems. We followed the uptake of 13C-labeled necromass by the bacterial and eukaryotic groundwater community quantitatively and over time by employing a combined protein and DNA stable isotope probing approach. Necromass was rapidly depleted in the mesocosms within four days, accompanied by a strong decrease of Shannon diversity and an increase of bacterial 16S rRNA gene copy numbers by one order of magnitude. Species of Flavobacterium, Massilia, Rheinheimera, Rhodoferax and Undibacterium dominated the microbial community within two days and were identified as key players in necromass degradation, based on a 13C incorporation of > 90% in their peptides. Their proteomes showed various uptake and transport related proteins, and many proteins involved in metabolizing amino acids. After four and eight days of incubation, autotrophic and mixotrophic groundwater species of Nitrosomonas, Limnohabitans, Paucibacter and Acidovorax increased in abundance, with a 13C incorporation between 0.5 and 23%. Our data point towards a very fast and exclusive uptake of labeled necromass by a few specialists followed by a concerted action of groundwater microorganisms, including autotrophs presumably fueled by released, reduced nitrogen and sulfur compounds generated during necromass degradation.
2022-05-31 | PXD031173 | Pride
Project description:The objectives of this study were to establish a microbiome profile for oral epithelial dysplasia using archival lesion swab samples to characterize the community variations and the functional potential of the microbiome using 16S rRNA gene sequencing
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Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome Randomized trial comparing azithromycin (AZM) treatment with placebo for eight weeks. Bronchoalveolar lavage (BAL) samples were obtained before and after treatment to explore the effects of AZM on microbiome, in the lower airways. 16S rRNA was quantified and sequenced (MiSeq) The amplicons from total 39 samples are barcoded and the barcode is provided in the metadata_complete.txt file.
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Project description:groundwater 16S rRNA gene amplicon sequencing
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Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.
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