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PROVIDER: PRJNA591432 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The respiratory tract microbiome in children with Cystic Fibrosis
| PRJNA311065 | ENA
Project description:The link between human gut microbiota (a complex group of microorganisms including not only bacteria but also fungi, viruses, etc.,) and the physiological state is nowadays unquestionable. Metaproteomic has emerged as a useful technique to characterize this microbial community, not just taxonomically, but also focusing on specific biological processes carried out by gut microbiota that may have an effect in the host health or pathological state. Cystic fibrosis is a genetic disease in which the microbiota of the respiratory tract determines the patient's survival and differences in composition of gut microbiota of cystic fibrosis patients respect to healthy infants have been reported. In order to characterize this host-microbiota inter-relation, we carried out the metaproteomic study of 30 stool samples from infants with cystic fibrosis.
2022-10-11 | PXD029284 | Pride
Project description:The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found between unrelated healthy controls and non-diabetic cystic fibrosis patients possessing Pseudomonas aeruginosa pulmonary tract infection. UPN727 cells were stimulated with autologous plasma (n=5), unrelated healthy control plasma (n=24), or plasma from patients with cystic fibrosis possessing Psuedomonas aeruginosa pulmonary tract infection (n=20). Gene expression analysis was perfromed in order to evaluate the transcriptional signature associated with cystic fibrosis.
2012-09-01 | E-GEOD-35711 | biostudies-arrayexpress
Project description:The nasal and bronchial epithelium are unified parts of the respiratory tract that are affected in the monogenic disorder cystic fibrosis (CF). Recent studies have uncovered that nasal and bronchial tissues exhibit intrinsic variability, including differences in mucociliary cell composition and expression of unique transcriptional regulatory proteins which relate to germ layer origin. In the present study, we explored transcriptomic differences between cultured nasal and bronchial epithelial cells from people with CF. Comparison of air-liquid interface-differentiated epithelial cells from subjects with CF revealed distinct mucociliary differentiation states of nasal and bronchial cultures. Moreover, using RNA sequencing we identified cell type-specific signature transcription factors in differentiated nasal and bronchial epithelial cells.
2023-11-21 | GSE241801 | GEO
Project description:Secondhand smoke exposure (SHSe) is a common environmental factor known to increase asthma severity and respiratory infections in children, as well disrupt metabolic signals and host immune responses in patients with cystic fibrosis (CF). This study defines biomarkers and metabolic profiles of SHSe (includes ENDS exposure) in the young CF population and determines how SHSe impacts regulation of infection, inflammation, and respiratory health.
2018-10-10 | ST001079 | MetabolomicsWorkbench
Project description:BACKGROUND. Lower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging since non-infectious respiratory illnesses appear clinically similar and existing microbiologic tests are often falsely negative or detect incidentally-carried microbes common in children. These challenges result in antimicrobial overuse and adverse patient outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and precision treatment remains unclear. METHODS. We used tracheal aspirate RNA-sequencing to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a random forest gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n=117) or of non-infectious respiratory failure (n=50). We then developed a classifier that integrates the: i) host LRTI probability, ii) abundance of respiratory viruses, and iii) dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm. RESULTS. The host classifier achieved a median AUC of 0.967 by 5-fold cross-validation, driven by activation markers of T cells, alveolar macrophages and the interferon response. The integrated classifier achieved a median AUC of 0.986 and significantly increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n=94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those. CONCLUSIONS. Lower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.
2022-12-06 | GSE212532 | GEO
Project description:Cystic fibrosis airway respiratory microbiome Raw sequence reads
| PRJNA615628 | ENA