Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1161162 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Soil microorganisms carry out decomposition of complex organic carbon molecules, such as chitin. High diversity of the soil microbiome and complexity of the soil habitat has posed a challenge to elucidate specific interactions between soil microorganisms. Here, we overcame this challenge by studying a model soil consortium (MSC-2) that is composed of 8 species. The MSC-2 isolates were originally obtained from the same soil that was enriched with chitin as a substrate. Our aim was to elucidate specific roles of the 8 member species during chitin metabolism in soil. The 8 species were added to sterile soil with chitin and incubated for 3 months. Multi-omics was used to understand how the community composition, transcript and protein expression and chitin-related metabolites shifted during the incubation period. The data clearly and consistently revealed a temporal shift during chitin decomposition and defined contributions by individual species. A Streptomyces species was a key player in early steps of chitin decomposition, followed by other members of MSC-2. These results illustrate how multi-omics applied to a defined consortium untangles complex interactions between soil microorganisms.
2025-02-01 | GSE251759 | GEO
Project description:Exoproteomics of Hopland soil isolates. Metabolic trait to efficiently utilize plant polymers provides the energy-expensive microbial adaptation to survive in low carbon availability soil.
2019-07-01 | MSV000084044 | MassIVE
Project description:Inferring in humans biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to M-^StranslateM-^T the results to humans. In this context, the Systems Biology Verification for Industrial Methodology for Process Verification in Research (SBV IMPROVER) initiative had run a Species Translation Challenge for the scientific community to explore and understand the limit of translatability from rodent to human using systems biology. Therefore, a multi-layer omics dataset was generated that comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, the generation, processing and quality control analysis of the multi-layer omics dataset. The datasets are accessible in public repositories could be leveraged for further translation studies.
2014-06-10 | E-MTAB-2091 | biostudies-arrayexpress
Project description:Biocrusts not only are considered ecosystem pioneers, but also have been recognized as a model system for soil ecosystem research. Furthermore, visually distinguishable phenotypic traits and stable physiological characteristics make biocrusts have significant advantages in meta-omics researches. So, we collected four types of biocrusts, applied metaproteome, to explore active microbial metabolism.
2021-08-02 | PXD027685 |
Project description:In this study, we analyzed transcriptome gene expression microarray, epigenomic miRNA microarray and methylome sequencing data simultaneously in PBMs from 5 high hip BMD subjects and 5 low hip BMD subjects. Through integrating the transcriptomic and epigenomic data, firstly we identified BMD-related genetic factors, including 9 protein coding genes and 2 miRNAs, of which 3 genes (FAM50A, ZNF473 and TMEM55B) and one miRNA (hsa-mir-4291) showed the consistent association evidence from both gene expression and methylation data, and 3 genes (TMEM55B, RNF40 and ALDOA) were confirmed in the meta-analysis of 7 GWAS samples and GEnetic Factors for OSteoporosis consortium (GEFOS-2) GWAS results. Secondly in network analysis we identified an interaction network module with 12 genes and 11 miRNAs including AKT1, STAT3, STAT5A, FLT3, hsa-mir-141 and hsa-mir-34a which have been associated with BMD in previous studies. This module revealed the crosstalk among miRNAs, mRNAs and DNA methylation and showed four potential regulatory patterns of gene expression to influence the BMD status, including regulation by gene methylation, by miRNA and its methylation, by transcription factors and co-regulation by miRNA and gene methylation. In conclusion, the integration of multiple layers of omics can yield more in-depth results than analysis of individual omics data respectively. Integrative analysis from transcriptomics and epigenomic data improves our ability to identify causal genetic factors, and more importantly uncover functional regulation pattern of multi-omics for osteoporosis etiology. 5 high hip BMD subjects and 5 low hip BMD subjects
2014-10-22 | E-GEOD-62588 | biostudies-arrayexpress
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.
2020-08-21 | PXD016242 | Pride
Project description:A multi-omics approach has revealed both common and distinctive cellular and molecular signatures of inflammation and immune dysregulation that characterize distinct phenotypes of human RAG deficiency.
2024-12-10 | GSE274284 | GEO