Ontology highlight
ABSTRACT:
PROVIDER: PRJNA741065 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Fire is a crucial event regulating the structure and functioning of many ecosystems. Yet few studies focused on how fire affects both the taxonomic and functional diversity of soil microbial communities, along with plant diversity and soil carbon (C) and nitrogen (N) dynamics. Here, we analyze these effects for a grassland ecosystem 9-months after an experimental fire at the Jasper Ridge Global Change Experiment (JRGCE) site in California, USA. Fire altered soil microbial communities considerably, with community assembly process analysis indicating that environmental selection pressure was higher in burned sites. However, a small subset of highly connected taxa were able to withstand the disturbance. In addition, fire decreased the relative abundances of most genes associated with C degradation and N cycling, implicating a slow-down of microbial processes linked to soil C and N dynamics. In contrast, fire stimulated plant growth, likely enhancing plant-microbe competition for soil inorganic N. To synthesize our findings, we performed structural equation modeling, which showed that plants but not microbial communities were responsible for the significantly higher soil respiration rates in burned sites. In conclusion, fire is well-documented to considerable alter the taxonomic and functional composition of soil microorganisms, along with the ecosystem functioning, thus arousing feedback of ecosystem responses to affect global climate.
2022-02-19 | GSE126737 | GEO
Project description:In this paper, we first report that EC smoking significantly increases the odds of gingival inflammation. Then, we seek to identify and explain the mechanism that underlies the relationship between EC smoking and gingival inflammation via the oral microbiome. We performed mediation analyses to assess if EC smoking affects the oral microbiome, which in turn affects gingival inflammation. For this, we collected saliva and subgingival samples from EC users and non-users and profiled their microbial compositions via 16S rRNA amplicon sequencing. We then performed α-diversity, β-diversity, and taxonomic differential analyses to survey the disparity in microbial composition between EC users and non-users. We found significant increases in α-diversity in EC users and disparities in β-diversity between EC users and non-users.
2022-12-09 | GSE201949 | GEO
Project description:Understanding microbial community diversity is thought to be crucial for improving process functioning and stabilities of wastewater treatment systems. However, current studies largely focus on taxonomic groups based on 16S rRNA, which are not necessarily linked to functioning, or a few selected functional genes. Here we launched a study to profile the overall functional genes of microbial communities in three full-scale wastewater treatment systems. Triplicate activated sludge samples from each system were analyzed using a high-throughput metagenomics tool named GeoChip 4.2, resulting in the detection of 38,507 to 40,647 functional genes. A high similarity of 75.5% to 79.7% shared genes was noted among the nine samples. Moreover, correlation analyses showed that the abundances of a wide array of functional genes were associated with system performances. For example, the abundances of overall nitrogen cycling genes had a strong correlation to total nitrogen (TN) removal rates (r = 0.7647, P < 0.01). The abundances of overall carbon cycling genes were moderately correlated with COD removal rates (r = 0.6515, P < 0.01). Lastly, we found that influent chemical oxygen demand (COD inf) and total phosphorus concentrations (TP inf), and dissolved oxygen (DO) concentrations were key environmental factors shaping the overall functional genes. Together, the results revealed vast functional gene diversity and some links between the functional gene compositions and microbe-mediated processes.
2014-12-31 | GSE53744 | GEO
Project description:Functional profiles predicted based on taxonomic affiliations differed from those obtained by GeoChip microarray analysis, which separated community functional capacity based on plant location. The identified metabolic pathways provided insight regarding microbial strategies for colonization and survival in these ecosystems.
2015-07-09 | GSE70539 | GEO
Project description:Functional profiles predicted based on taxonomic affiliations differed from those obtained by GeoChip microarray analysis, which separated community functional capacity based on plant location. The identified metabolic pathways provided insight regarding microbial strategies for colonization and survival in these ecosystems. Sixteen samples analyzed.
2015-07-09 | E-GEOD-70539 | biostudies-arrayexpress
Project description:An increasing body of evidence suggests an important role of the human microbiome in health and disease. We propose a ‘lost and found’ pipeline, which examines high quality unmapped sequence reads for microbial taxonomic classification. Using this pipeline, we are able to detect bacterial and archaeal phyla in blood using RNA sequencing (RNA-Seq) data. Careful analyses, including the use of positive and negative control datasets, suggest that these detected phyla represent true microbial communities in whole blood and are not due to contaminants. We applied our pipeline to study the composition of microbial communities present in blood across 192 individuals from four subject groups: schizophrenia (n=48), amyotrophic lateral sclerosis (n=47), bipolar disorder (n=48) and healthy controls (n=49). We observe a significantly increased microbial diversity in schizophrenia compared to the three other groups and replicate this finding in an independent schizophrenia case-control study. Our results demonstrate the potential use of total RNA to study microbes that inhabit the human body.
2016-05-25 | GSE80974 | GEO
Project description:Tandem mass spectrometry based shotgun proteomics of distal gut microbiomes is exceedingly difficult due to the inherent complexity and taxonomic diversity of the samples. We introduce two new methodologies to improve metaproteomic studies of microbiome samples. These methods include the stable isotope labeling in mammals to permit protein quantitation across the two mouse cohorts, as well as the application of activity-based probes to enrich and analyze both host and microbial proteins with specific functionalities. We used these technologies to study the microbiota from the adoptive T cell transfer mouse model of inflammatory bowel disease (IBD) and compare these samples to an isogenic control; thereby, limiting genetic and environmental variables that influence microbiome composition.
2017-01-16 | PXD005667 | Pride