Nasal microbiome quantification using different sampling methods
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB32021 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3426238.fastq.gz | Fastqsanger.gz | |||
| ERR3426239.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 2 of 2 |
Similar Datasets
Project description:Bacteria need nutrients from the host environment to survive, yet we know little about which biochemicals are present in the airways (the metabolome), which of these biochemicals are essential for bacterial growth and how they change with airway disease. The aims of this pilot study were to develop and compare methodologies for sampling the upper and lower airway metabolomes and to identify biochemicals present in the airways that could potentially support bacterial growth. Eight healthy human volunteers were sampled by four methods: two standard approaches - nasal lavage and induced sputum, and two using a novel platform, synthetic adsorptive matrix (SAM) strips-nasosorption and bronchosorption. Collected samples were analyzed by Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Five hundred and eighty-one biochemicals were recovered from the airways belonging to a range of metabolomic super-pathways. We observed significant differences between the sampling approaches. Significantly more biochemicals were recovered when SAM strips were used, compared to standard sampling techniques. A range of biochemicals that could support bacterial growth were detected in the different samples. This work demonstrates for the first time that SAM strips are a highly effective method for sampling the airway metabolome. This work will assist further studies to understand how changes in the airway metabolome affect bacterial infection in patients with underlying airway disease.
2019-06-13 | MTBLS179 | MetaboLights
Project description:Considering the complex and multifarious features of Chronic rhinosinusitis (CRS) including immunologic patterns, novel modalities are needed to reflect clinical and pathophysiological endotypes beyond nasal polyps.We aimed to investigate the proteome of nasal secretions on filter paper from CRS patients to characterize endotypes.
2019-07-29 | PXD013330 | Pride
Project description:In bottom-up proteomics, data are acquired on peptides resulting from proteolysis. In XIC-based quantification, the quality of the protein abundance estimation depends on how peptide data are filtered and on which quantification method is used to sum up peptide intensities into protein abundances. So far, these two questions have been addressed independently. Here, we studied to which extent the relative performances of the quantification methods depend on the filters applied on peptide intensity data. To this end, we performed a spike-in experiment using Universal Protein Standard (UPS1) to evaluate the performances of five quantification methods, including TOP3, iBAQ, Average of all peptide intensities or log-intensities and intensity modeling, in five datasets obtained after application of four peptide filters based on peptide sharing between proteins, retention time variability, peptides occurrence and peptide intensity profiles. We showed that estimated protein abundances were not equally affected by filters depending on the computation mode (sum or average) and the type of data (intensity or log intensity) used in the quantification methods and that filters could have contrasting effects depending on the quantification objective (absolute or relative). Our results also indicate that intensity modeling was the most robust method, providing the best results in absence of any filter, but that the different quantification methods can reach similar performances when appropriate peptide filters are used. Altogether, our findings provide clues to best handle intensity data according to the quantification objective and to the experimental design.
2018-11-14 | PXD009740 | Pride
Project description:Background: Asthma, a complex chronic lung disease affecting the airways, has striking disparities across ancestral groups, but the molecular underpinning of these differences is poorly understood and minimally studied. A major goal of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to understand multi-omics signatures of asthma risk in the nasal epithelium focusing on populations of African ancestry. Methods: DNA methylation (DNAm) quantification was performed using Illumina’s Infinium MethylationEPIC array® using genomic DNA from nasal airway epithelial cells collected across the 4 US recruitment sites (Baltimore, Chicago, Denver, and Washington DC) for 331 subjects (N=149 asthma cases, N= 182 never asthmatic controls). We performed association analysis to identify eQTMs (CpG-gene associations) for DEGs limiting to CpGs ≤5kb from the transcription start site or within enhancer regions identified through promoter-capture HiC in bronchial epithelial cells. CpGs from significant eQTMs (p<0.05) were tested for differential methylation by asthma (DMCs) to assess the relative contribution of expression and methylation in asthma risk. All models were fully adjusted for ancestry, sampling site, and appropriate latent factors. Findings: Multi-omic analysis identified FKBP5 as a key contributor to asthma risk, where the association between nasal epithelium gene expression is likely regulated by methylation and is associated with increased use of inhaled corticosteroids. FKBP5 is a co-chaperone of glucocorticoid receptor signaling and known to be involved in drug response in asthma. Interpretation: Our analyses reveal genes and networks in asthma that are differentially expressed in nasal epithelium of current asthma cases of African ancestry in CAAPA. Importantly, this work reveals molecular dysregulation on three axes – increased Th2 inflammation, decreased capacity for wound healing, and impaired drug response – that may play a critical role in asthma within the African Diaspora.
2023-12-23 | GSE250513 | GEO
Project description:Objectives: To determine whether disease processes related to granulomatosis with polyangiitis (GPA) are reflected in gene expression profiles of nasal mucosa. Methods: Nasal brushings of the inferior turbinate were obtained from 32 patients with GPA (10 with active nasal disease, 13 with prior nasal disease, 9 with no history of nasal disease) and a composite comparator group with and without inflammatory nasal disease (12 healthy people, 15 with sarcoidosis, 8 with allergic rhinitis). Differential gene expression was assessed between subgroups of GPA and comparators. Results: 339 genes were differentially expressed between the GPA and comparator groups (absolute fold change > 1.5; false discovery rate < 0.05). Top canonical pathways upregulated in nasal brushings from patients with GPA include granulocyte adhesion and diapedesis (p=8.6 E-22), agranulocyte adhesion and diapedesis (p=1.3 E-14), interleukin 10 signaling (3.0 E-11), and TREM1 signaling (9.0 E-11). A set of genes differentially expressed in GPA independent of nasal disease activity status included genes related to epithelial barrier integrity (fibronectin 1, desmosomal proteins) and several matricellular proteins (e.g. osteonectin, osteopontin). Significant overlap of differentially expressed genes was observed between active and prior nasal disease GPA subgroups. Peripheral blood neutrophil and mononuclear gene expression levels associated with GPA were similarly altered in the nasal gene expression profiles of patients with active or prior nasal disease. Conclusions: Profiling the nasal transcriptome in GPA reveals gene expression signatures related to innate immunity, inflammatory cell chemotaxis, extracellular matrix composition, and epithelial barrier integrity. Airway-based expression profiling is feasible and informative in GPA.
2018-08-29 | GSE119136 | GEO
Project description:Bacterial communities in different tillage methods
| PRJEB46144 | ENA
Project description:Fungal communities in different tillage methods
| PRJEB46147 | ENA
Project description:Previous studies showed that olfactory cues are important for mammalian communication. However, many specific compounds that convey information between conspecifics are still unknown. To understand mechanisms and functions of olfactory cues, olfactory signals such as volatile compounds emitted from individuals need to be assessed. Sampling of animals with and without scent glands was typically conducted using cotton swabs rubbed over the skin or fur and analysed by gas chromatography-mass spectrometry (GC-MS). However, this method has various drawbacks, including a high level of contaminations. Thus, we adapted two methods of volatile sampling from other research fields and compared them to sampling with cotton swabs. To do so we assessed the body odor of common marmosets (Callithrix jacchus) using cotton swabs, thermal desorption (TD) tubes and, alternatively, a mobile GC-MS device containing a thermal desorption trap. Overall, TD tubes comprised most compounds (N = 113), with half of those compounds being volatile (N = 52). The mobile GC-MS captured the fewest compounds (N = 35), of which all were volatile. Cotton swabs contained an intermediate number of compounds (N = 55), but very few volatiles (N = 10). Almost all compounds found with the mobile GC-MS were also captured with TD tubes (94%). Hence, we recommend TD tubes for state of the art sampling of body odor of mammals or other vertebrates, particularly for field studies, as they can be easily transported, stored and analysed with high performance instruments in the lab. Nevertheless, cotton swabs capture compounds which still may contribute to the body odor, e.g. after bacterial fermentation, while profiles from mobile GC-MS include only the most abundant volatiles of the body odor.
| S-EPMC5571906 | biostudies-literature
Project description:The impact of repeated sample collection on COVID-19 test performance is unknown. The FDA and CDC currently recommend the primary collection of diagnostic samples to minimize the perceived risk of false-negative findings. We therefore evaluated the association between repeated sample collection and test performance among 325 symptomatic patients undergoing COVID-19 testing in Atlanta, GA. High concordance was found between consecutively collected mid-turbinate samples with both molecular (n = 74, 100% concordance) and antigen-based (n = 147, 97% concordance, kappa = 0.95, CI = 0.88-1.00) diagnostic assays. Repeated sample collection does not decrease COVID-19 test performance, demonstrating that multiple samples can be collected for assay validation and clinical diagnosis.
| S-EPMC8295385 | biostudies-literature