Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1208564 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Dibamus cf. smithi (Smith's blind skink) genome, rDibSmi1, haplotype 2
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Project description:Cystic fibrosis (CF), a genetic disorder, is characterized by chronic lung disease. Small non-coding RNAs are key regulators of gene expression and participate in various processes, which are dysregulated in CF; however, they remain poorly studied. Here, we determined the complete microRNAs (miRNAs) expression pattern in three CF ex-vivo models. The miRNA profiles of air-liquid interface cultures of airway epithelia (bronchi, nasal cells, and nasal polyps) samples from patients with CF and non-CF controls were obtained by deep sequencing. Compared with non-CF controls, several miRNAs were deregulated in CF samples, for instance miR-181a-5p and the miR-449 family were upregulated. Moreover, mature miRNAs often showed variations (i.e., isomiRs) relative to their reference sequence, such as miR-101, suggesting that miRNAs consist of heterogeneous repertoires of multiple isoforms with different effects on gene expression. Analysis of miR-181a-5p and miR-101-3p roles indicated that they regulate the expression of WISP1, a key component of cell proliferation/migration programs. We showed that miR-101 and miR-181a-5p participated in aberrant recapitulation of wound healing programs by controlling WISP1 mRNA and protein level. Our miRNA expression data bring new insights into CF physiopathology and define new potential therapeutic targets in CF
2020-10-21 | GSE159708 | GEO
Project description:Rapid evaporative ionisation mass spectrometry (REIMS) is a novel technique for the real-time analysis of biological material. It works by conducting an electrical current through a sample, causing it to rapidly heat and evaporate, with the analyte containing vapour channelled to a mass spectrometer. It was used to characterise the metabolome of 45 Pseudomonas aeruginosa (P. aeruginosa) isolates from cystic fibrosis (CF) patients and compared to 80 non-CF P. aeruginosa. Phospholipids gave the highest signal intensity; 17 rhamnolipids and 18 quorum sensing molecules were detected, demonstrating that REIMS has potential for the study of virulence-related metabolites. P. aeruginosa isolates obtained from respiratory samples showed a higher diversity, which was attributed to the chronic nature of most respiratory infections. The analytical sensitivity of REIMS allowed the detection of a metabolome that could be used to classify individual P. aeruginosa isolates after repeated culturing with 81% accuracy, and an average 83% concordance with multilocus sequence typing. This study underpins the capacities of REIMS as a tool with clinical applications, such as metabolic phenotyping of the important CF pathogen P. aeruginosa, and highlights the potential of metabolic fingerprinting for fine scale characterisation at a sub-species level.
2022-01-26 | MTBLS644 | MetaboLights