Human lung metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB18482 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This was a pilot study aimed at uncovering the role of myeloid-derived suppressor cells (myeloid-derived suppressor cell) in patients with Tuberculosis and differences between cells found in peripheral blood and in the lung. Fluidigm™ RT-PCR technology was used to quantify expression levels of 43 genes in monocytecytes and myeloid-derived suppressor cell from peripheral blood and monocytecytes and alveolar macrophages from bronchoalveolar lavage fluid taken from patients with Tuberculosis or other lung diseases.
2022-02-22 | GSE197113 | GEO
Project description:metagenomic next-generation sequencing of bronchoalveolar lavage fluid
| PRJNA974201 | ENA
Project description:Bronchoalveolar lavage samples collected from lung transplant recipients. Numeric portion of sample name is an arbitrary patient ID and AxBx number indicates the perivascular (A) and bronchiolar (B) scores from biopsies collected on the same day as the BAL fluid was collected. Several patients have more than one sample in this series and can be determined by patient number followed by a lower case letter. Acute rejection state is determined by the combined A and B score - specifically, a combined AB score of 2 or greater is considered an acute rejection. Keywords = Bronchoalveolar lavage Keywords = lung transplant Keywords: other
2004-11-30 | GSE2018 | GEO
Project description:Comparison of Bacterial Communities in Bronchoalveolar Lavage between a U.S. and Malawi Population.
| PRJNA253931 | ENA
Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome Randomized trial comparing azithromycin (AZM) treatment with placebo for eight weeks. Bronchoalveolar lavage (BAL) samples were obtained before and after treatment to explore the effects of AZM on microbiome, in the lower airways. 16S rRNA was quantified and sequenced (MiSeq) The amplicons from total 39 samples are barcoded and the barcode is provided in the metadata_complete.txt file.
2016-07-19 | E-GEOD-74396 | biostudies-arrayexpress
Project description:Recent progress in unbiased metagenomic next-generation sequencing (mNGS) allows simultaneous examination of microbial and host genetic material in a single test. Leveraging affordable bronchoalveolar lavage fluid (BALF) mNGS data, we employed machine learning to create a diagnostic approach distinguishing lung cancer from pulmonary infections, conditions prone to misdiagnosis in clinical settings. This prospective study analyzed BALF-mNGS data from lung cancer and pulmonary infection patients, delineating differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction derived from copy number variation (CNV). Integrating these metrics into a host/microbe metagenomics-driven machine learning model (Model VI) demonstrated robustness, achieving an AUC of 0.87 (95% CI = 0.857-0.883), sensitivity = 73.8%, and specificity = 84.5% in the training cohort, and an AUC of 0.831 (95% CI = 0.819-0.843), sensitivity = 67.1%, and specificity = 94.4% in the validation cohort for distinguishing lung cancer from pulmonary infections. The application of a rule-in and rule-out strategy-based composite predictive model significantly enhances accuracy (ACC) in distinguishing between lung cancer and tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These findings highlight the potential of cost-effective mNGS-based analysis as a valuable tool for early differentiation between lung cancer and pulmonary infections, offering significant benefits through a single comprehensive testing.
2024-01-08 | GSE252118 | GEO
Project description:Sub-Saharan Africa represents 69% of the total number of individuals living with HIV infection worldwide and 72% of AIDS deaths globally. Pulmonary infection is a common and frequently fatal complication, though little is known regarding the lower airway microbiome composition of this population. Our objectives were to characterize the lower airway microbiome of Ugandan HIV-infected patients with pneumonia, to determine relationships with demographic, clinical, immunological, and microbiological variables and to compare the composition and predicted metagenome of these communities to a comparable cohort of patients in the US (San Francisco). Bronchoalveolar lavage samples from a cohort of 60 Ugandan HIV-infected patients with acute pneumonia were collected. Amplified 16S ribosomal RNA was profiled and aforementioned relationships examined. Ugandan airway microbiome composition and predicted metagenomic function were compared to US HIV-infected pneumonia patients. Among the most common bacterial pulmonary pathogens, Pseudomonas aeruginosa was most prevalent in the Ugandan cohort. Patients with a richer and more diverse airway microbiome exhibited lower bacterial burden, enrichment of members of the Lachnospiraceae and sulfur-reducing bacteria and reduced expression of TNF-alpha and matrix metalloproteinase-9. Compared to San Franciscan patients, Ugandan airway microbiome were significantly richer, and compositionally distinct with predicted metagenomes that encoded a multitude of distinct pathogenic pathways e.g secretion systems. Ugandan pneumonia-associated airway microbiome is compositionally and functionally distinct from those detected in comparable patients in developed countries, a feature which may contribute to adverse outcomes in this population. Please note that the data from the comparable cohort of patients in the USUS data was published as supplemental material of PMID: 22760045 but not submitted to GEO The 'patient_info.txt' contains 12 clinical, 7 immunological and 3 microbiological variables for each patient. The G2 PhyloChip microarray platform (commercially available from Second Genome, Inc.) was used to profile bacteria in lower airway samples from 60 subjects
2014-02-20 | E-GEOD-52791 | biostudies-arrayexpress
Project description:Analysis of lung microbiota from the bronchoalveolar lavage fluid of patients with acute severe respiratory distress syndrome
| PRJDB10129 | ENA
Project description:Bronchoalveolar lavage specimens collected from lung cancer patients, and analyzed using mass spectrometry-based quantitative N-glycoproteomic technique.
2020-05-27 | MSV000085469 | MassIVE
Project description:Establish a pipeline for identifying bacterial peptides from human bronchoalveolar lavage fluid samples.
2019-06-24 | PXD008273 | Pride