Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1311598 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Full title: Environmental transcriptome analysis of LfeRT32a in its natural microbial community comparing the biofilm and planktonic modes of life. Extreme acidic environments are characterized among other features by the high metal content and the lack of nutrients (oligotrophy). Macroscopic biofilms and filaments usually grow on the water-air interface or under the stream attached to solid substrates (streamers). In the Tinto River (Spain), brown filaments develop under the water stream where the Gram-negative iron-oxidizing bacteria Leptospirillum ferrooxidans and Acidithiobacillus ferrooxidans are abundant. Both microorganisms play a critical role in bioleaching processes for industrial (biominery) and environmental applications (acid mine drainage, bioremediation). The aim of this study was to investigate the physiological differences between the free living (planktonic) and the sessile (biofilm associated) lifestyles of L. ferrooxidans as part of a natural extremely acidophilic community.
2016-06-23 | GSE20267 | GEO
Project description:Benthic stream biofilm Targeted Locus (Loci)
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Project description:California stream benthic algae Raw sequence reads
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Project description:Multiple stressor effects on stream benthic bacteria
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Project description:Total RNA extracted from the head and neck cell line CAL165 were purified using miRNeasy minikit (Qiagen). RNA libraries were then generated with the NEB next small library prep set for SOLID (New England Biolabs) and sequenced on the Applied Biosystems SOLiD 5500 wildfire system following the manufacturer's instructions.
2017-06-07 | GSE89510 | GEO
Project description:Metabarcoding study of soil fungi following wildfire
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Project description:Climate change is impacting human health through a historic rise in wildfire smoke across the United States and the world. Whereas the deleterious effects of wildfire smoke and associated air pollution on asthma outcomes are well-established epidemiologically, genetic risks and molecular mechanisms of how wildfire smoke affects asthma are unknown. This knowledge gap hinders the identification of high-risk individuals and the creation of targeted therapies or recommendations to protect these individuals. Here, we employ a genetic approach to identify common variant (minor allele frequency > 0.05) exposure-conditional genetic risk variants that localize with genomic responses to wood smoke particles (WSP), a model of wildfire smoke exposure, and associate with asthma in the Genetic Epidemiology Research on Aging (GERA) cohort. Our novel approach used nascent transcriptional signatures derived from WSP-exposed Beas-2B airway epithelial cells to reduce the genome sequence for discovery and allow a permutation-based statistical approach to identify 52 candidate SNPs. We applied biologic and bioinformatic filters to prioritize variants for direct testing of allele-dependent transcriptional regulatory function in plasmid reporters. The rs3861144 variant identified by this approach controls WSP responses of airway epithelial cells to SPRY2, which we showed is involved in mechanical injury repair in cell culture. Our results demonstrate that wildfire particulates contribute to asthma risk at the molecular level, and we have identified mechanistic targets and genetic variant candidates to apply for clinical risk prediction and development of targeted therapies for high-risk individuals.
2024-12-02 | GSE283113 | GEO