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
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.
Project description:Transcriptional profiling of methanotrophic bacteria (pmoA gene) in methane oxidation biocover soil by depth Three-different depth condition in methane oxidation biocover soil: top, middle and botton layer soil: genomic DNA extract. Three replicate per array.
Project description:Evaluation of short-read-only, long-read-only, and hybrid assembly approaches on metagenomic samples demonstrating how they affect gene and protein prediction which is relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic-based protein predictions.