Ontology highlight
ABSTRACT:
PROVIDER: PRJNA543333 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9073890_1.fastq.gz | Fastqsanger.gz | |||
| SRR9073890_2.fastq.gz | Fastqsanger.gz | |||
| SRR9073891_1.fastq.gz | Fastqsanger.gz | |||
| SRR9073891_2.fastq.gz | Fastqsanger.gz | |||
| SRR9073892_1.fastq.gz | Fastqsanger.gz |
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Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
2016-08-02 | E-GEOD-85064 | biostudies-arrayexpress
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | GEO
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).
2016-04-01 | E-GEOD-55293 | biostudies-arrayexpress
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
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Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
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2013-10-30 | GSE51592 | GEO
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:Anaerobic digestion is a popular and effective microbial process for waste treatment. The performance of anaerobic digestion processes is contingent on the balance of the microbial food web in utilizing various substrates. Recently, co-digestion, i.e., supplementing the primary substrate with an organic-rich co-substrate has been exploited to improve waste treatment efficiency. Yet the potential effects of elevated organic loading on microbial functional gene community remains elusive. In this study, functional gene array (GeoChip 5.0) was used to assess the response of microbial community to the addition of poultry waste in anaerobic digesters treating dairy manure. Consistent with 16S rRNA gene sequences data, GeoChip data showed that microbial community compositions were significantly shifted in favor of copiotrophic populations by co-digestion, as taxa with higher rRNA gene copy number such as Bacilli were enriched. The acetoclastic methanogen Methanosarcina was also enriched, while Methanosaeta was unaltered but more abundant than Methanosarcina throughout the study period. The microbial functional diversity involved in anaerobic digestion were also increased under co-digestion.
2017-01-12 | GSE93419 | GEO
Project description:Accurate description of a microbial community is an important first step in understanding the role of its components in ecosystem function. A method for surveying microbial communities termed Serial Analysis of Ribosomal DNA (SARD) is described here. Through a series of molecular cloning steps, short DNA sequence tags are recovered from the fifth variable (V5) region of the prokaryotic 16S rRNA gene from microbial communities. These tags are ligated to form concatemers comprised of 20-40 tags which are cloned and identified by DNA sequencing. Four agricultural soil samples were profiled with SARD to assess the method’s utility. A total of 37,008 SARD tags comprising 3,127 unique sequences were identified. Comparison of duplicate profiles from one soil genomic DNA preparation revealed the method was highly reproducible. The large numbers of singleton tags together with non-parametric richness estimates indicated a significant amount of sequence tag diversity remained undetected with this level of sampling. The abundance classes of the observed tags were scale-free and conformed to a power law distribution. Numerically, the majority of the total tags observed belonged to abundance classes that were each present at less than 1% of the community. Over 99% of the unique tags individually made up less than 1% of the community. Therefore, from either numerical or diversity standpoints, low abundant taxa comprised a significant proportion of the microbial communities examined and could potentially make a large contribution to ecosystem function. SARD may provide a means to explore the ecological role of these rare members of microbial communities in qualitative and quantitative terms. Keywords: SARD profiles, culture-independent study, microbial community survey, microbial census
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