Forest soil metagenom of Nacetin site
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB17634 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| ERR5731420.fastq.gz | Fastqsanger.gz | |||
| ERR5731420_1.fastq.gz | Fastqsanger.gz | |||
| ERR5731420_2.fastq.gz | Fastqsanger.gz | |||
| ERR5731430.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 144 |
Similar Datasets
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).
2022-03-14 | PXD004428 | Pride
Project description:Evidence shows that bacteria contribute actively to the decomposition of cellulose and hemicellulose in forest soil; however, their role in this process is still unclear. Here we performed the screening and identification of bacteria showing potential cellulolytic activity from litter and organic soil of a temperate oak forest. The genomes of three cellulolytic isolates previously described as abundant in this ecosystem were sequenced and their proteomes were characterized during the growth on plant biomass and on microcrystalline cellulose. Pedobacter and Mucilaginibacter showed complex enzymatic systems containing highly diverse carbohydrate-active enzymes for the degradation of cellulose and hemicellulose, which were functionally redundant for endoglucanases, -glucosidases, endoxylanases, -xylosidases, mannosidases and carbohydrate-binding modules. Luteibacter did not express any glycosyl hydrolases traditionally recognized as cellulases. Instead, cellulose decomposition was likely performed by an expressed GH23 family protein containing a cellulose-binding domain. Interestingly, the presence of plant lignocellulose as well as crystalline cellulose both trigger the production of a wide set of hydrolytic proteins including cellulases, hemicellulases and other glycosyl hydrolases. Our findings highlight the extensive and unexplored structural diversity of enzymatic systems in cellulolytic soil bacteria and indicate the roles of multiple abundant bacterial taxa in the decomposition of cellulose and other plant polysaccharides.
2016-05-02 | PXD003844 | Pride
Project description:Forest soil bacterial community Raw sequence reads
| PRJNA429723 | ENA
Project description:Anthropogenic nitrogen (N) deposition may affect soil organic carbon (SOC) decomposition, thus affecting the global terrestrial carbon (C) cycle. However, it remains unclear how the level of N deposition affects SOC decomposition by regulating microbial community composition and function, especially C-cycling functional genes structure. We investigated the effects of short-term N addition on soil microbial C-cycling functional gene composition, SOC-degrading enzyme activities, and CO2 emission in a 5-year field experiment established in an artificial Pinus tabulaeformis forest on the Loess Plateau, China.
2022-03-01 | GSE147041 | GEO
Project description:Despite the global importance of forests, it is virtually unknown how their soil microbial communities adapt at the phylogenetic and functional level to long term metal pollution. Studying twelve sites located along two distinct gradients of metal pollution in Southern Poland revealed that both community composition (via MiSeq Illumina sequencing of 16S rRNA genes) and functional gene potential (using GeoChip 4.2) were highly similar across the gradients despite drastically diverging metal contamination levels. Metal pollution level significantly impacted microbial community structure (p = 0.037), but not bacterial taxon richness. Metal pollution altered the relative abundance of specific bacterial taxa, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes and Proteobacteria. Also, a group of metal resistance genes showed significant correlations with metal concentrations in soil, although no clear impact of metal pollution levels on overall functional diversity and structure of microbial communities was observed. While screens of phylogenetic marker genes, such as 16S rRNA, provided only limited insight into resilience mechanisms, analysis of specific functional genes, e.g. involved in metal resistance, appeared to be a more promising strategy. This study showed that the effect of metal pollution on soil microbial communities was not straightforward, but could be filtered out from natural variation and habitat factors by multivariate statistical analysis and spatial sampling involving separate pollution gradients.
2014-07-22 | GSE59620 | GEO