Ontology highlight
ABSTRACT:
PROVIDER: PRJNA659414 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12533348_1.fastq.gz | Fastqsanger.gz | |||
| SRR12533348_2.fastq.gz | Fastqsanger.gz | |||
| SRR12533349_1.fastq.gz | Fastqsanger.gz | |||
| SRR12533349_2.fastq.gz | Fastqsanger.gz | |||
| SRR12533350_1.fastq.gz | Fastqsanger.gz |
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Project description:Global warming has shifted climate zones poleward or upward. However, understanding the responses and mechanism of microbial community structure and functions relevant to natural climate zone succession is challenged by the high complexity of microbial communities. Here, we examined soil microbial community in three broadleaved forests located in the Wulu Mountain (WLM, temperate climate), Funiu Mountain (FNM, at the border of temperate and subtropical climate zones), or Shennongjia Mountain (SNJ, subtropical climate).Soils were characterized for geochemistry, Illumina sequencing was used to determine microbial taxonomic communities and GeoChips 5.0 were used to determine microbial functional genes.
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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.
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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 EarthM-bM-^@M-^Ys 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. Fifty four samples were collected from three soil types (Phaeozem,Cambisol,Acrisol) in three sites (Hailun, Fengqiu and Yingtan) along a latitude with reciprocal transplant; Both with and without maize cropping in each site; Three replicates in every treatments.
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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.
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Project description:A study of soil bacterial diversity during vegetation succession in riparian zones
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Project description:Soils are a huge reservoir of organic C, and the efflux of CO2 from soils is one of the largest fluxes in the global C cycle. Out of all natural environments, soils probably contain the greatest microbial biomass and diversity, which classifies them as one of the most challenging habitats for microbiologists (Mocali and Benedetti, 2010). Until today, it is not well understood how soil microorganisms will respond to a warmer climate. Warming may give competitive advantage to species adapted to higher temperatures (Rinnan et al., 2009). The mechanisms behind temperature adaptations of soil microbes could be shifts within the microbial community. How microbial communities will ultimately respond to climate change, however, is still a matter of speculation. As a post-genomic approach in nature, metaproteomics allows the simultaneous examination of various protein functions and responses, and therefore is perfectly suited to investigate the complex interplay between respiration dynamics, microbial community architecture, and ecosystem functioning in a changing environment (Bastida et al., 2012). Thereby we will gain new insights into responses to climate change from a microbial perspective. Our study site was located at 910 m a.s.l. in the North Tyrolean Limestone Alps, near Achenkirch, Austria The 130 year-old mountain forests consist of Norway spruce (Picea abies) with inter-spread of European beech (Fagus sylvatica) and silver fir (Abies alba). Three experimental plots with 2 × 2 m warmed- and control- subplots were installed in 2004. The temperature difference between control and warmed plots was set to 4 °C at 5 cm soil depth. Soil was warmed during snow-free seasons. In order to extract proteins from forest soil samples, the SDS–phenol method was adopted as previously described by Keiblinger et al. (2012). Protein extractions were performed from each subplot soil samples. The abundance of protein-assigned microbial phylogenetic and functional groups, were calculated based on the normalized spectral abundance factor (NSAF, Zybailov et al., 2006).
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