Ontology highlight
ABSTRACT:
PROVIDER: PRJNA888465 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:2D (A549) and 3D (AIR-606) human lung epithelial cell cultures were mock treated or exposed to 100 ug/ml petroleum coke or urban air particulates (both in the PM10 range) for 16 h. Secretomes were compared for triplicate treatments for each group by isobaric tags and LC/MS/MS.
2018-03-26 | PXD005194 | Pride
Project description:Asthma and chronic obstructive pulmonary disease (COPD) are influenced by interactions between genetic background and environmental exposures such as air pollutants, yet the mechanisms linking genetic variation and pollutant response remain poorly understood. We used nascent RNA run-on sequencing to characterize transcriptional responses of lung cells exposed to wood smoke particles, urban particulate matter, and Afghan dust particles. These datasets provide the first characterization of the nascent transcriptional response to urban particulate matter in primary lung cells and reveal both shared and pollutant-specific regulatory dynamics. Integration with regulatory network inference and genetic association data enables prioritization of noncoding variants and candidate regulatory mechanisms linking environmental exposures to lung disease risk.
2026-04-30 | GSE327419 | GEO
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2023-03-23 | E-MTAB-12477 | biostudies-arrayexpress
Project description:This study aimed to shed light on the gene regulatory networks underlying plant leaf responses to air particulate matter. Our investigation focused on autochthonous shrubs of laurel (Laurus nobilis L.) grown in pots located in two contrasting areas: a highly polluted traffic road and rural countryside within the same town (Altopascio, Lucca, Italy). RNA-seq data were related to leaf morphological traits and air particulate matter, allowing to identify key players in modulating the capabilities of plants to phyllo-remediate high air particulate matter levels in urban environment.
2023-03-16 | E-MTAB-12332 | biostudies-arrayexpress
Project description:In the present study, we investigate pulmonary transcriptional responses in mice following exposure in situ to ambient air in a heavily polluted urban environment. Mature C57BL/CBA male mice were caged in sheds located in an urban area near two working steel mills and a major highway in Hamilton, Ontario, Canada. Control mice were housed in the same environment but received only high-efficiency particle-filtered air. Whole lung tissues were collected from mice exposed for 3 weeks, 10 weeks or for 10 weeks followed by 6 weeks in the laboratory (16 weeks total). DNA microarrays were used to explore changes in pulmonary gene expression in mice breathing ambient air versus HEPA-filtered air. Transcriptional profiling revealed changes in the expression of genes implicated in the lipid droplet synthesis pathway (plin, dgat2, lpl, s3-12, agpat2), antioxidants (ucp1). We postulate that exposure to particulate matter adsorbed with polycyclic aromatic hydrocarbons triggers lipid droplet synthesis (holding depots for lipids and malformed/excess proteins tagged for degradation) in the lungs, which act to sequester particulates adsorbed with toxic chemicals. Increased lipid droplet synthesis could potentially lead to endogenous/stressor-induced synthesis of reactive oxygen species and activation of antioxidant mechanisms. Further investigation into the stimulation of lipid droplet synthesis in the lung in response to air pollution is warranted in order to better understand these mechanistic changes and the resulting health implications.
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Project description:Asthma and chronic obstructive pulmonary disease (COPD) are lung diseases strongly influenced by interactions between genetic background and environmental exposures, particularly air pollutants. However, the biological mechanisms by which genetic variation and pollutant exposure impact disease remain poorly understood. Interpretation of genome-wide association studies is limited because most disease-associated variants occur in noncoding regions and are difficult to connect to functional regulatory mechanisms and downstream gene targets. Here, we integrate nascent RNA run-on sequencing with regulatory network inference to identify pollutant-responsive transcriptional regulatory elements and their upstream regulators in lung cells. Using newly generated and published datasets, we analyze multiomics responses to multiple air pollutants, including wood smoke particles, urban particulate matter, and Afghan dust particles. These analyses provide the first characterization of the nascent transcriptional response to urban particulate matter in primary lung cells and reveal both shared and pollutant-specific regulatory dynamics. We then integrate pollutant-responsive regulatory networks with genetic associations for asthma and COPD to prioritize noncoding variants for experimental validation. By linking these variants to candidate transcription factors and target genes, we identify mechanisms through which environmental exposures may interact with noncoding genetic variants to influence disease risk. This framework enables functional interpretation of noncoding variants through environmentally responsive transcriptional networks.
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