Ontology highlight
ABSTRACT:
PROVIDER: PRJNA980971 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24958800.fastq.gz | Fastqsanger.gz | |||
| SRR24958801.fastq.gz | Fastqsanger.gz | |||
| SRR24958802.fastq.gz | Fastqsanger.gz | |||
| SRR24958803.fastq.gz | Fastqsanger.gz | |||
| SRR24958804.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 42 |
Similar Datasets
Project description:The purpose of this study was to characterize global gene expression in human airway epithelial cells and identify cellular pathways associated with coarse, fine and ultrafine particulate matter (PM) exposures. Ambient PM was collected in 3 different size fractions from Chapel Hill air, particles were extracted from foam or filter matrices and lyophilized. Human primary airway epithelial cells were exposed to particles at 250μg/ml or vehicle control for 6h in culture. Following exposure, RNA was isolated and hybridized to human HG U133A affymetrix chips. Experiment Overall Design: Human primary epithelial cells were exposed to coarse, fine, ultrafine PM or vehicle control in culture for 6h. Three biological replicates for each treatment (coarse, fine, ultrafine, control) were conducted at (250ug/ml). 12 Affymetrix chips (HG U133A) were used.
2008-06-15 | E-GEOD-7010 | biostudies-arrayexpress
Project description:Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in E. coli for >2000 proteins over >60 growth conditions, including nutrient limitations, non-metabolic stresses and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.
2021-04-06 | GSE139983 | GEO
Project description:Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in E. coli for >2000 proteins over >60 growth conditions, including nutrient limitations, non-metabolic stresses and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of larg e-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.
2021-03-11 | PXD014948 | Pride
Project description:Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in E. coli for >2000 proteins over >60 growth conditions, including nutrient limitations, non-metabolic stresses and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.
2022-01-12 | PXD017258 | panorama
Project description:Carbon Cloth Bioreactor Addition Community Raw sequence reads
| PRJNA792791 | ENA