Human metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA48479 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Human Microbiome Project (HMP) Metagenomic WGS Projects, deeper sequencing of the human microbiome samples: Mock Pilot
| PRJNA48475 | ENA
Project description:Human Microbiome Project (HMP) Metagenomic WGS Projects, deeper sequencing of the human microbiome samples: Clinical Pilot
| PRJNA48477 | ENA
Project description:EMG produced TPA metagenomics assembly of the Human Microbiome Project (HMP) Metagenomic WGS Projects, deeper sequencing of the human microbiome samples: Production Phase (human metagenome) data set
| PRJEB22283 | ENA
Project description:Deeper shotgun sequencing of human microbiome samples for the Human Microbiome Project (HMP)
| PRJNA43017 | ENA
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.
2022-02-17 | PXD025505 | Pride
Project description:Metagenomic sequencing data of human gut microbiome
| EGAD00001007735 | EGA
Project description:This project reanalzyes data from 4 other projects. Information about the samples can be found in the following four publications. The four samples used in this study include a ocean metaproteome sample, a human sample, a E. coli sample, and a Plamodium falciparum sample. B. N. Pease, E. L. Huttlin, M. P. Jedrychowski, E. Talevich, J. Harmon, T. Dillman, N. Kannan, C. Doerig, R. Chakrabarti, S. P. Gygi, and D. Chakrabarti. Global analysis of protein expression and phosphorylation of three stages of Plasmodium falciparum intraerythrocytic development. Journal of Proteome Research, 12:4028–4045, 2013. Damon H. May, Emma Timmins-Schiffman, Molly P. Mikan, H. Rodger Harvey, Elhanan Borenstein, Brook L. Nunn, and William S. Noble. An alignment-free metapeptide strategy for metaproteomic characterization of microbiome samples using shotgun metagenomic sequencing. Journal of Proteome Research, 15(8):2697–2705, 2016. PMID: 27396978. M. Kim, S. M. Pinto, D. Getnet, R. S. Nirujogi, S. S. Manda, R. Chaerkady, A. K. Madugundu, D. S. Kelkar, R. Isserlin, S. Jain, et al. A draft map of the human proteome. Nature, 509(7502):575–581, 2014. Hansjrg G ̋tzke, Claudio Muheim, A.F. Maarten Altelaar, Albert J.R. Heck, Gianluca Maddalo, and Daniel O. Daley. Identification of putative substrates for the periplasmic chaperone yfgm in Escherichia coli using quantitative proteomics. Molecular & Cellular Proteomics, 14(1):216–226, 2015.
2018-09-19 | PXD009265 | Pride
Project description:Production projects for the human ENCODE project
| PRJNA63441 | ENA
Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
2012-03-19 | E-GEOD-31075 | biostudies-arrayexpress
Project description:Dysbiotic configurations of the human gut microbiota have been linked with colorectal cancer (CRC). Human small non-coding RNAs are also implicated in CRC and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis but their role is less explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens of patients with CRC, or adenomas, and healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We reported a considerable overlap and correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. Furthermore, we identified a combined predictive signature composed by 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC from healthy and adenoma samples (AUC= 0.87). In summary we reported evidence that host-microbiome dysbiosis in CRC can be observed also by altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more accurate tools for diagnostic purposes.
2019-08-30 | GSE132236 | GEO