Ontology highlight
ABSTRACT:
PROVIDER: PRJNA826714 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
2016-06-15 | E-GEOD-68712 | biostudies-arrayexpress
Project description:Nowadays, many innovative omics-based technologies are used in toxicogenomic and risk assessment studies to investigate and identify changes in gene expression and protein levels. Recently, it became clear that the biological response for many compounds might depend on the moment of exposure (time-of-day), a phenomenon referred to as chronotoxicity. However, in most toxicogenomic and risk assessment studies, the temporal variations in gene expression caused by the circadian clock are neglected. These temporal variations can influence the outcome of omics- based experiments. In the present study, we investigated the impact of the circadian clock on the response of the liver transcriptome and acute toxicity of mice exposed to the chemotherapeutic agent cyclophosphamide at defined time points during the day.
2014-12-31 | GSE46035 | GEO
Project description:Raw mass spectrometry data of effluent samples from 15 wastewater treatment plants in two cities, China
| MSV000092880 | MassIVE
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.
2016-06-15 | GSE68712 | GEO
Project description:Background - The coronavirus disease 2019 (COVID-19) is rapidly spreading in China and more than 30 countries over last two months. COVID-19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily observed number of confirmed cases, and the intervention effects of implemented quarantine and control measures. Methods - We develop a Susceptible, Un-quanrantined infected, Quarantined infected, Confirmed infected (SUQC) model to characterize the dynamics of COVID-19 and explicitly parameterize the intervention effects of control measures, which is more suitable for analysis than other existing epidemic models. Results - The SUQC model is applied to the daily released data of the confirmed infections to analyze the outbreak of COVID-19 in Wuhan, Hubei (excluding Wuhan), China (excluding Hubei) and four first-tier cities of China. We found that, before January 30, 2020, all these regions except Beijing had a reproductive number R > 1, and after January 30, all regions had a reproductive number R lesser than 1, indicating that the quarantine and control measures are effective in preventing the spread of COVID-19. The confirmation rate of Wuhan estimated by our model is 0.0643, substantially lower than that of Hubei excluding Wuhan (0.1914), and that of China excluding Hubei (0.2189), but it jumps to 0.3229 after February 12 when clinical evidence was adopted in new diagnosis guidelines. The number of unquarantined infected cases in Wuhan on February 12, 2020 is estimated to be 3,509 and declines to 334 on February 21, 2020. After fitting the model with data as of February 21, 2020, we predict that the end time of COVID-19 in Wuhan and Hubei is around late March, around mid March for China excluding Hubei, and before early March 2020 for the four tier-one cities. A total of 80,511 individuals are estimated to be infected in China, among which 49,510 are from Wuhan, 17,679 from Hubei (excluding Wuhan), and the rest 13,322 from other regions of China (excluding Hubei). Note that the estimates are from a deterministic ODE model and should be interpreted with some uncertainty. Conclusions - We suggest that rigorous quarantine and control measures should be kept before early March in Beijing, Shanghai, Guangzhou and Shenzhen, and before late March in Hubei. The model can also be useful to predict the trend of epidemic and provide quantitative guide for other countries at high risk of outbreak, such as South Korea, Japan, Italy and Iran.
2024-09-02 | BIOMD0000000962 | BioModels
Project description:Landfill leachates and leachate scaling sample Raw sequence reads
| PRJNA706864 | ENA
Project description:Examining the impact of short term exposure to HDPE and PVC plastic leachates on gene transcription in Prochlorococcus cultures in vitro
2018-12-01 | GSE118155 | GEO