Bacteria and fungi
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA505085 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8186520_1.fastq.gz | Fastqsanger.gz | |||
| SRR8186520_2.fastq.gz | Fastqsanger.gz | |||
| SRR8186530_1.fastq.gz | Fastqsanger.gz | |||
| SRR8186530_2.fastq.gz | Fastqsanger.gz | |||
| SRR8186540_1.fastq.gz | Fastqsanger.gz |
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Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+–N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics.
2013-07-13 | GSE48820 | GEO
Project description:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes.
2015-05-23 | GSE69171 | GEO
Project description:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes. 300 samples were collected from 30 sites along the latitudinal gradient, with 10 replicates in every site
2015-05-23 | E-GEOD-69171 | biostudies-arrayexpress
Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+M-bM-^@M-^SN and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics. Twelve samples were collected from four elevations (3200, 3400, 3600 and 3800 m) along a Tibetan grassland; Three replicates in every elevation
2013-07-13 | E-GEOD-48820 | biostudies-arrayexpress
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:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities We used lignin degradation as a model process to demonstrate the use of an oligonucleotide microarray for directly detecting gene expression in soil communities using signal amplification instead of template amplification to avoid the introduction of PCR bias. In the current study, we analyzed mRNA isolated from two distinct soil microbial communities and demonstrate our ability to detect the expression of a small subset of lignin degrading genes following exposure to a lignitic substrate. We also included purified control amplicons and mixed target experiments with pure P. chrysosporium genomic cDNA to determine the level of interference from soil biomass on target hybridization.
2010-05-18 | E-GEOD-13977 | biostudies-arrayexpress
Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
2009-06-01 | GSE13977 | GEO
Project description:Due to its high altitude and extreme climate conditions, the Tibetan plateau is a region vulnerable to the impact of climate changes and anthropogenic perturbation, thus understanding how its microbial communities function may be of high importance. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, aiming to explore potential microbial responses to climate changes and anthropogenic perturbation. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities in treatment site were distinct, compared with those in control site, e.g. shrubland vs grassland, grazing site vs ungrazing site, or warmer site vs colder site. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes.
2013-11-16 | GSE52425 | GEO
Project description:To study long-term elevated CO2 and enriched N deposition interactive effects on microbial community and soil ecoprocess, here we investigated soil microbial community in a grassland ecosystem subjected to ambient CO2 (aCO2, 368 ppm), elevated CO2 (eCO2, 560 ppm), ambient nitrogen deposition (aN) or elevated nitrogen deposition (eN) treatments for a decade. There exist antagonistic CO2×N interactions on microbial functional genes associated with C, N, P S cycling processes. More strong antagonistic CO2×N interactions are observed on C degradation genes than other genes. Remarkably antagonistic CO2×N interactions on soil microbial communities could enhance soil C accumulation.
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Project description:Soil water repellency (SWR) (i.e. soil hydrophobicity or decreased soil wettability) is a major cause of global soil degradation and a key agricultural concern. This metabolomics data will support the larger effort measuring soil water repellency and soil aggregate formation caused by microbial community composition through a combination of the standard drop penetration test, transmission electron microscopy characterization and physico-chemical analyses of soil aggregates at 6 timepoints. Model soils created from clay/sand mixtures as described in Kallenbach et al. (2016, Nature Communications) with sterile, ground pine litter as a carbon/nitrogen source were inoculated with 15 different microbial communities known to have significantly different compositions based on 16S rRNA sequencing. This data will allow assessment of the direct influence of microbial community composition on soil water repellency and soil aggregate stability, which are main causes of soil degradation.
The work (proposal:https://doi.org/10.46936/10.25585/60001346) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.
2024-02-14 | MSV000094090 | MassIVE