Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
Project description:DNA, RNA and protein were extracted from the culture and subjected to massive parallel sequencing and nano-LC-MS-MS respectively Combination of these methods enabled the reconstruction of the complete genome sequence of M oxyfera from the metagenome and identification of the functionally relevant enzymes and genes
Project description:Sequencing the metatranscriptome can provide information about the response of organisms to varying environmental conditions. We present a methodology for obtaining random whole-community mRNA from a complex microbial assemblage using Pyrosequencing. The metatranscriptome had, with minimum contamination by ribosomal RNA, significant coverage of abundant transcripts, and included significantly more potentially novel proteins than in the metagenome. Keywords: metatranscriptome, mesocosm, ocean acidification
Project description:The fate of the carbon stocked in permafrost soils following global warming and permafrost thaw is of major concern in view of the potential for increased CH4 and CO2 emissions from these soils. Complex carbon compound degradation and greenhouse gas emissions are due to soil microbial communities, but their composition and functional potential in permafrost soils are largely unknown. Here, a 2 m deep permafrost and its overlying active layer soil were subjected to metagenome sequencing, quantitative PCR, and microarray analyses. The active layer soil and 2 m permafrost soil microbial community structures were very similar, with Actinobacteria being the dominant phylum. The two soils also possessed a highly similar spectrum of functional genes, especially when compared to other already published metagenomes. Key genes related to methane generation, methane oxidation and organic matter degradation were highly diverse for both soils in the metagenomic libraries and some (e.g. pmoA) showed relatively high abundance in qPCR assays. Genes related to nitrogen fixation and ammonia oxidation, which could have important roles following climatic change in these nitrogen-limited environments, showed low diversity but high abundance. The 2 m permafrost soil showed lower abundance and diversity for all the assessed genes and taxa. Experimental biases were also evaluated and showed that the whole community genome amplification technique used caused large representational biases in the metagenomic libraries. This study described for the first time the detailed functional potential of permafrost-affected soils and detected several genes and microorganisms that could have crucial importance following permafrost thaw. A 2m deep permafrost sample and it overlying active layer were sampled and their metagenome analysed. For microarray analyses, 8 other soil samples from the same region were used for comparison purposes.
Project description:This data set contains 1376 mass spectrometry reads from root, rhizosphere and leaf sample of Populus Trichocarpa, as well as associated controls. This metabolomics data set was collected as part of a larger campaign which complements the metabolomics data with metagenome sequencing, transcriptomics, and soil measurement data.
Project description:The aim of this study was to identify TBBPA-degrading organisms in a complex microbial community by a metagenome-based functional metaproteomic approach, using protein-based stable isotope probing (protein-SIP). Firstly, the degradation kinetics were evaluated in order to simulate the decrease of residual mass of the labelled compound based on experimental data. In sequence, a metagenome was generated, and biomass was collected in different time-points for protein-SIP in incubations with 13C-TBBPA. This approach allowed for the identification organisms assimilating labelled carbon from the cometabolic degradation of a micropollutant.
Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
Project description:Many diseases have been associated with gut microbiome abnormalities. The root cause of such diseases is not only due to bacterial dysbiosis, but also to change in bacterial functions, which are best studied by proteomic approaches. Although bacterial proteomics is well established, metaproteomics is hindered by challenges associated with the sample physical structure, contaminating proteins, the simultaneous analysis of hundreds of species and the subsequent data analysis. Here, we present a systematic assessment of sample preparation and data analysis methodologies applied to LC-MS/MS metaproteomics experiment. We could show that low speed centrifugation (LSC) has a significant impact on both peptide identifications and reproducibility. LSC led to increase in peptide and proteins identifications compare to no LSC. Notably, the dominant bacterial phyla, i.e. Firmicutes and Bacteroidetes, showed divergent representation between LSC and no-LSC. In terms of data processing, protein sequence databases derived from mouse faeces metagenome provided at least four times more MS/MS identification compared to databases of concatenated single organisms. We also demonstrated that two-steps database search strategy comes at the expense of a dramatic rise in number of false positives compared to single-step strategy. Overall, we found a positive correlation between matching metaproteome and metagenome abundance, which could be linked to core microbial functions, such as glycolysis-gluconeogenesis, citrate cycle and carbon metabolism. We observed significant overlap and correlation at the phylum, class, order and family taxonomic levels between taxonomy-derived from metagenome and metaproteome. Notably, nearly all functional categories (e.g., membrane transport, translation, transcription) were differentially abundant in the metaproteome (activity) compared to what would be expected from the metagenome (potential). In conclusion, these results highlight the need to perform metaproteomics when studying complex microbiome samples.