Project description:Land cover change has long been recognized that marked effect the amount of soil organic carbon. However, little is known about microbial-mediated effect processes and mechanism on soil organic carbon. In this study, the soil samples in a degenerated succession from alpine meadow to alpine steppe meadow in Qinghai-Tibetan Plateau degenerated, were analyzed by using GeoChip functional gene arrays.
Project description:The association between soil microbes and plant roots is present in all natural and agricultural environments. Microbes can be beneficial, pathogenic, or neutral to the host plant development and adaptation to abiotic or biotic stresses. Progress in investigating the functions and changes in microbial communities in diverse environments have been rapidly developing in recent years, but the changes in root function is still largely understudied. The aim of this study was to determine how soil bacteria influence maize root transcription and microRNAs (miRNAs) populations in a controlled inoculation of known microbes over a defined time course. At each time point after inoculation of the maize inbred line B73 with ten bacterial isolates, DNA and RNA were isolated from roots. The V4 region of the 16S rRNA gene was amplified from the DNA and sequenced with the Illumina MiSeq platform. Amplicon sequencing of the 16S rRNA gene indicated that most of the microbes successfully colonized maize roots. The colonization was dynamic over time and varied with the specific bacterial isolate. Small RNA sequencing and mRNA-Seq was done to capture changes in the root transcriptome from 0.5 to 480 hours after inoculation. The transcriptome and small RNA analyses revealed epigenetic and transcriptional changes in roots due to the microbial inoculation. This research provides the foundational data needed to understand how plant roots interact with bacterial partners and will be used to develop predictive models for root response to bacteria.
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
Project description:Isolation of bacteria in infected brains in patients with Parkinson's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).
Project description:Isolation of bacteria in infected brains in patients with Parkinson's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).
Project description:Comparison of probe-target dissociations of probe Eub338 and Gam42a with native RNA of P. putida, in vitro transcribed 16s rRNA of P. putida, in vitro transcribed 16S rRNA of a 2,4,6-trinitrotoluene contaminated soil and an uncontaminated soil sample. Functional ANOVA revealed no significant differences in the dissociation curves of probe Eub338 when hybridised to the different samples. On the opposite, the dissociation curve of probe Gam42a with native RNA of P. putida was significantly different than the dissociation curves obtained with in vitro transcribed 16S rRNA samples. Keywords: Microbial diversity, thermal dissociation analysis, CodeLink microarray
Project description:Microplastics (MPs) as widespread contamination pose high risk for aquatic organisms.Intestinal microbiotahas have high interaction with immune system of host body. In this study, intestinal microbiota of zebrafish after Polystyrene (PS-MPs) exposure were characterized by 16S rDNA amplicon sequencing. We found that 100nm and 200μm PS-MPs exposure significantly increased diversity of intestinal microbiota and all the three sizes of PS-MPs increased abundance of pathogenic bacteria.
Project description:Anthropogenic activities have dramatically increased the inputs of reactive nitrogen (N) into terrestrial ecosystems, with potentially important effects on the soil microbial community and consequently soil C and N dynamics. Our analysis of microbial communities in soils subjected to 14 years of 7 g N m-2 year-1 Ca(NO3)2 amendment in a Californian grassland showed that the taxonomic composition of bacterial communities, examined by 16S rRNA gene amplicon sequencing, was significantly altered by nitrate amendment, supporting the hypothesis that N amendment- induced increased nutrient availability, yielded more fast-growing bacterial taxa while reduced slow-growing bacterial taxa. Nitrate amendment significantly increased genes associated with labile C degradation (e.g. amyA and xylA) but had no effect or decreased the relative abundances of genes associated with degradation of more recalcitrant C (e.g. mannanase and chitinase), as shown by data from GeoChip targeting a wide variety of functional genes. The abundances of most N cycling genes remained unchanged or decreased except for increases in both the nifH gene (associated with N fixation), and the amoA gene (associated with nitrification) concurrent with increases of ammonia-oxidizing bacteria. Based on those observations, we propose a conceptual model to illustrate how changes of functional microbial communities may correspond to soil C and N accumulation.
Project description:The melting of permafrost and its potential impact on greenhouse gas emissions is a major concern in the context of global warming. The fate of the carbon trapped in permafrost will largely depend on soil physico-chemical characteristics, among which are the quality and quantity of organic matter, pH and water content, and on microbial community composition. In this study, we used microarrays and real-time PCR (qPCR) targeting 16S rRNA genes to characterize the bacterial communities in three different soil types representative of various Arctic settings. The microbiological data were linked to soil physico-chemical characteristics and CO2 production rates. Microarray results indicated that soil characteristics, and especially the soil pH, were important parameters in structuring the bacterial communities at the genera/species levels. Shifts in community structure were also visible at the phyla/class levels, with the soil CO2 production rate being positively correlated to the relative abundance of the Alphaproteobacteria, Bacteroidetes, and Betaproteobacteria. These results indicate that CO2 production in Arctic soils does not only depend on the environmental conditions, but also on the presence of specific groups of bacteria that have the capacity to actively degrade soil carbon.