Project description:Wood-decomposition in terrestrial ecosystems is a very important process with huge ecologic consequences. This decomposition process is a combination of biological respiration, leaching and fragmentation, mainly triggered by organismic activities. In order to gain a deeper insight into these microbial communities and their role in deadwood decay, we used metaproteomics. Metaproteomics is an important tool and offers the ability to characterize the protein complement of environmental microbiota at a given point in time. In this dataset, we provide data of an exemplary beech wood log and applied different extraction methods to provide the proteome profile of beech dead wood and their corresponding fungal-bacterial community.
2020-05-27 | PXD016801 | Pride
Project description:Comparison of DNA extraction methods for human gut microbial community profiling
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.
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.
Project description:Microbial decomposition of soil organic carbon (SOC) in Arctic permafrost is one of the most important, but poorly understood, factors in determining the greenhouse gas feedback of tundra ecosystems to climate. Here, we examine changes in the structure of microbial communities in an anoxic incubation experiment at either –2 or 8 °C for up to 122 days using both an organic and a mineral soil collected from the Barrow Environmental Observatory in northern Alaska, USA. Soils were characterized for SOC and geochemistry, and GeoChips 5.0 were used to determine microbial community structure and functional genes associated with C availability and Fe(III) reduction.
2016-11-09 | GSE89644 | GEO
Project description:16S rRNA and ITS2 profiling of deadwood associated microbial community
Project description:Recent advances in (meta)genomic methods have provided new opportunities to examine host-microbe-environment interactions in the human gut. While opportunities exist to extract DNA from freshly sourced colonic tissue there are potentially valuable sources of DNA from historical studies that might also be examined. We examined how four different tissue DNA extraction methods employed in past clinical trials might impact the recovery of microbial DNA from a colonic tissue sample as assessed using a custom designed phylogenetic microarray for human gut bacteria and archaebacteria. While all methods of DNA extraction produced similar phylogenetic profiles some extraction specific biases were also observed. Real time PCR analysis targeting several bacterial groups substantiated this observation. These data suggest that while the efficacy of different DNA extraction methods differs somewhat all the methods tested produce an accurate representation of microbial diversity. This suggests that DNA samples archived in biobanks should be suitable for retrospective analyses.
Project description:The goal of this study was to optimize protein extraction methods to study root-associated bacteria in maize. For this we inoculated sterile maize plants with a synthetic community composed of seven different bacteria (Ben Niu et al. PNAS 2017, vol 114, n 12). Then, we extracted proteins from maize roots using eight different protein extraction methods in triplicates. These methods were a combination of different extraction buffers (SDS or Triton-based) and mechanical disruption methods (bead-beating, N2 grinding, glass homogenizer and freeze-thaw cycles). We found that vortexing maize roots with glass beads in PBS yielded the highest numbers of microbial protein identification.
