Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1078335 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.
2009-08-06 | E-GEOD-17156 | biostudies-arrayexpress
Project description:Bordetella bronchiseptica is a gram-negative respiratory pathogen that causes a diverse spectrum of respiratory disease in a wide-range of hosts. We sought to determine if strains of B. bronchiseptica differed in virulence using the mouse model of infection. Mean lethal doses (LD50) of different B. bronchiseptica strains varied widely in the murine model. B. bronchiseptica strain 253 had a LD50 that was 10-fold lower than the prototypical and fully sequenced B. bronchiseptica strain RB50. Using whole genomic transcriptome analysis covering 100% of B. bronchisetpctica strain RB50ÃÂs predicted open reading frames (ORFs), 253 was identified as lacking expression of adenylate cyclase toxin (ACT). Using whole genomic comparative genomic hybridization analysis and whole genome sequencing, we determined that the cya operon, which is required for ACT production, was absent from the 253 genome.
2007-10-01 | E-MEXP-1205 | biostudies-arrayexpress
Project description:Respiratory syncytial virus (RSV) is a prevalent pathogen globally, can cause severe disease in older adults, and remains the leading cause of bronchiolitis and pneumonia in the United States for children during their first year of life. Despite its prevalence worldwide, RSV specific pharmacologic interventions remain unavailable for most infected patients. Although vaccines are available for a subset of adults, further investigation of the molecular interactions between RSV and the host remains essential to understanding this prolific pathogen. To aid our understanding of the host response in both RSV infected cells, and uninfected bystanders, we utilized single-cell RNA sequencing.
2025-04-16 | GSE281623 | GEO
Project description:<p>Accurate tests for microbiologic diagnosis of lower respiratory tract infections (LRTI) are needed. Gene expression profiling of whole blood represents a powerful new approach for analysis of the host response during respiratory infection that can be used to supplement pathogen detection testing. Using qPCR, we prospectively validated the differential expression of 10 genes previously shown to discriminate bacterial and non-bacterial LRTI confirming the utility of this approach. In addition, a novel approach using RNAseq analysis identified 141 genes differentially expressed in LRTI subjects with bacterial infection. Using "pathway-informed" dimension reduction, we identified a novel 11 gene set (selected from lymphocyte, α-linoleic acid metabolism, and IGF regulation pathways) and demonstrated a predictive accuracy for bacterial LRTI (nested CV-AUC=0.87). RNAseq represents a new and an unbiased tool to evaluate host gene expression for the diagnosis of LRTI.</p>
| phs001248 | dbGaP
Project description:Hypoxia is a common microenvironmental condition in the mucus-obstructed, infected, and inflamed airways of lung disease patients and is known to influence immune responses in the lungs. However, the effects of hypoxia on lung host defence against respiratory bacterial infections relevant to chronic pulmonary disease are less understood. Nontypeable Haemophilus influenzae (NTHi), an opportunistic respiratory pathogen, frequently colonizes the lower airways of patients with chronic lung diseases and is associated with poor clinical outcomes. Human ex vivo lung explants were infected with a clinical strain of NTHi under normoxic and hypoxic conditions for 24 hours. The host response to infection and the effect of hypoxia were investigated using RNA sequencing.
2024-11-07 | GSE280966 | GEO
Project description:Diagnosis of acute respiratory viral infection is currentlybased on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals.
2009-08-06 | GSE17156 | GEO
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