Ontology highlight
ABSTRACT:
PROVIDER: PRJNA437560 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR6820490_1.fastq.gz | Fastqsanger.gz | |||
| SRR6820490_2.fastq.gz | Fastqsanger.gz | |||
| SRR6820500_1.fastq.gz | Fastqsanger.gz | |||
| SRR6820500_2.fastq.gz | Fastqsanger.gz |
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Project description:Microbial communities that degrade lignocellulosic biomass are typified by high levels of species- and strain-level complexity, as well as synergistic interactions between both cellulolytic and non-cellulolytic microorganisms. Here we deconvoluted a highly efficient cellulose-degrading and methanogenic consortium (SEM1b) that is co-dominated by Clostridium (Ruminiclostridium) thermocellum and multiple heterogenic strains affiliated to C. proteolyticus. A time-series analysis was performed over the entire lifetime span of the microbial community and comprised of metagenomic, metatranscriptomic, metabolomics, metaproteomic and 16S rRNA gene analysis for 8 time points, in triplicate. Metagenomic analysis of SEM1b recovered metagenome-assembled genomes (MAGs) for each constituent population, whereas in parallel two novel strains of C. proteolyticus were isolated and sequenced. Both the recovered MAGs and the isolated strains were used as a database for further functional meta-omics. Absolute quantitative metatranscriptomics was performed thanks the spike-in of an in vitro transcribed RNA as an internal standard and label-free quantification was used for the metaproteomic analysis. The present dataset has been used for several publications. The first aim of the project was to characterize the interactions between uncultured populations in a lignocellulose-degrading community. Furthermore, because of the in-depth multi-omics characterization of the community, the dataset was used to develop new approaches for meta-omics integration as well as to assess the protein-to-RNA ratio of multiple microbial populations simultaneously. Modifications of multi-omics toolkits allowed us to assess the linearity between transcriptome and proteome for each population over time and reveal deeper functional-related trends and integrative co-dependent metabolisms that drive the overall phenotype of microbial communities.
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Project description:Waste decomposition in landfills is a complex and microbe-mediated process. Understanding the microbial community composition and structure is critical for accelerating decomposition and reducing adverse impact on the environment. Here, we examined the microbial communities along with landfill depth and age (LDA) in a sanitary landfill in Beijing, China using 16s rRNA Illumina sequencing and GeoChip 4.6. We found that Clostridiales and Methanofollis were the predominant bacteria and archaea in the present landfill, respectively. Interestingly, in contrast with the decreasing trend of microbial diversity in soil, both phylogenetic and functional diversities were higher in deeper and older refuse in the landfill. Phylogenetic compositions were obviously different in the refuse with the same LDA and such difference is mainly attributed to the heterogeneity of refuse instead of random process. Nevertheless, functional structures were similar within the same LDA, indicating that microbial community assembly in the landfill may be better reflected by functional genes rather than phylogenetic identity. Mantel test and canonical correspondence analysis suggested that environmental variables had significant impacts on both phylogenetic composition and functional structure. Higher stress genes, genes for degrading toxic substances and endemic genes in deeper and older refuse indicated that they were needed for the microorganisms to survive in the more severe environments. This study suggests that landfills are a repository of stress-resistant and contaminant-degrading microorganisms, which can be used for accelerating landfill stabilization and enhancing in situ degradation. Fifteen refuse samples with five landfill depths and ages (6m/2a, 12m/4a, 18m/6a, 24m/8a and 30m/10a) were collected from a sanitary landfill in Beijing, China. Three replicates in every landfill depth and age
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