Ontology highlight
ABSTRACT:
PROVIDER: PRJNA993600 | ENA |
REPOSITORIES: ENA
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Project description:Recent progress in unbiased metagenomic next-generation sequencing (mNGS) allows simultaneous examination of microbial and host genetic material in a single test. Leveraging affordable bronchoalveolar lavage fluid (BALF) mNGS data, we employed machine learning to create a diagnostic approach distinguishing lung cancer from pulmonary infections, conditions prone to misdiagnosis in clinical settings. This prospective study analyzed BALF-mNGS data from lung cancer and pulmonary infection patients, delineating differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction derived from copy number variation (CNV). Integrating these metrics into a host/microbe metagenomics-driven machine learning model (Model VI) demonstrated robustness, achieving an AUC of 0.87 (95% CI = 0.857-0.883), sensitivity = 73.8%, and specificity = 84.5% in the training cohort, and an AUC of 0.831 (95% CI = 0.819-0.843), sensitivity = 67.1%, and specificity = 94.4% in the validation cohort for distinguishing lung cancer from pulmonary infections. The application of a rule-in and rule-out strategy-based composite predictive model significantly enhances accuracy (ACC) in distinguishing between lung cancer and tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These findings highlight the potential of cost-effective mNGS-based analysis as a valuable tool for early differentiation between lung cancer and pulmonary infections, offering significant benefits through a single comprehensive testing.
2024-01-08 | GSE252118 | GEO
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:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
2013-10-30 | GSE51592 | GEO
Project description:Microbe-microbe interactions are critical for gut microbiome function. A challenging task to understand health and disease-related microbiome signatures is to move beyond descriptive community-level profiling towards disentangling microbial interaction networks. Here, we aimed to determine members taking on a keystone role in shaping the community ecology of a widely used synthetic bacterial community (OMM12).
2022-11-14 | MSV000090704 | MassIVE
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in EarthM-bM-^@M-^Ys biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling. Fifty four samples were collected from three soil types (Phaeozem,Cambisol,Acrisol) in three sites (Hailun, Fengqiu and Yingtan) along a latitude with reciprocal transplant; Both with and without maize cropping in each site; Three replicates in every treatments.
2013-10-30 | E-GEOD-51592 | biostudies-arrayexpress
Project description:Known as “The Oriental Botanic Garden” and the natural gene bank of biological species, Shennongjia is one of the most biologically diverse areas in China and a member of UNESCO's World Network of Biosphere Reserves. The macro-organism resources of shennongjia have been deeply explored. However, the microbial community structure was scarcely detected. In this study, we aim to detedect the microbial community along six sites of Shennonajia Mountain and explore the major controlling factor in shaping microbial community with a microarray-based metagenomics tool named GeoChip 4.2.
2014-06-13 | GSE58433 | GEO
Project description:Known as M-bM-^@M-^\The Oriental Botanic GardenM-bM-^@M-^] and the natural gene bank of biological species, Shennongjia is one of the most biologically diverse areas in China and a member of UNESCO's World Network of Biosphere Reserves. The macro-organism resources of shennongjia have been deeply explored. However, the microbial community structure was scarcely detected. In this study, we aim to detedect the microbial community along six sites of Shennonajia Mountain and explore the major controlling factor in shaping microbial community with a microarray-based metagenomics tool named GeoChip 4.2. Seventy-three samples were collected from six sites along the Shennongjia Mountain, with 5-15 replicates in every site
2014-06-13 | E-GEOD-58433 | biostudies-arrayexpress
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | GEO
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
2016-08-02 | E-GEOD-85064 | biostudies-arrayexpress