RNA-sequencing of primary and secondary bacterial pneumonia
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA821208 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18520121_1.fastq.gz | Fastqsanger.gz | |||
| SRR18520121_2.fastq.gz | Fastqsanger.gz | |||
| SRR18520122_1.fastq.gz | Fastqsanger.gz | |||
| SRR18520122_2.fastq.gz | Fastqsanger.gz | |||
| SRR18520123_1.fastq.gz | Fastqsanger.gz |
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Project description:A leading cause of morbidity and mortality during influenza infection is the development of a secondary bacterial pneumonia, which is appropriately treated with antibiotics. In the absence of a bacterial superinfection, prescribing antibiotics is not indicated but has nevertheless become a common clinical practice for those presenting with a respiratory viral illness. We found that antibiotic use during an antecedent influenza infection impaired the lung innate immunologic defenses toward a secondary challenge with methicillin-resistantStaphylococcus aureus(MRSA). The antibiotics perturbed the gut microbiome causing a fungal dysbiosis that drives an increase in lung eosinophils. We also demonstrate eosinophils, through the release of major basic protein, impair macrophage ability to clear MRSA. Moreover, we provide clinical evidence that eosinophils positively correlate with antibiotic use and worsened outcomes in patients hospitalized for viral infections. Altogether, our work establishes a counterproductive effect of antibiotic treatment during influenza infection that have negative immunologic consequences in the lungs thereby increasing the risk of developing a secondary bacterial infection.
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Project description:Introduction: Diagnosis of severe influenza pneumonia remains challenging because of the lack of correlation between presence of influenza virus and patient’s clinical status. We conducted gene expression profiling in the whole blood of critically ill patients to identify a gene signature that would allow clinicians to distinguish influenza infection from other causes of severe respiratory failure (e.g. bacterial pneumonia, non-infective systemic inflammatory response syndrome). Methods: Whole blood samples were collected from critically ill individuals and assayed on Illumina HT-12 gene expression beadarrays. Differentially expressed genes were determined by linear mixed model analysis and over-represented biological pathways determined using GeneGo MetaCore. Results: The gene expression profile of H1N1 influenza A pneumonia was distinctly different from bacterial pneumonia and systemic inflammatory response syndrome. The influenza gene expression profile is characterized by up-regulation of genes from cell cycle regulation, apoptosis and DNA-damage response pathways. In contrast, no distinctive gene-expression signature was found in patients with bacterial pneumonia or systemic inflammatory response syndrome. The gene expression profile of influenza infection persisted through five days of follow-up. Furthermore, in patients with primary H1N1 influenza A infection who subsequently developed bacterial co-infection, the influenza gene-expression signature remained unaltered, despite the presence of a super-imposed bacterial infection. Conclusions: The whole blood expression profiling data indicates that the host response to influenza pneumonia is distinctly different from that caused by bacterial pathogens. This information may speed up identification of the cause of infection in patients presenting with severe respiratory failure, allowing appropriate patient care to be undertaken more rapidly. Daily PAXgene samples for up to 5 days for; influenza A pneumonia patients (n=8), bacterial pneumonia patients (n=16), mixed bacterial and influenza A pneumonia patients (n=3), systemic inflammatory response patients (SIRS, n=13). Days 1 and 5 PAXgene samples for healthy control individuals
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Project description:Pneumonia stands as the primary cause of death among children under five, with its onset attributed to a broad spectrum of microorganisms. Diagnosis poses an ongoing challenge, relying on clinical or microbiological criteria, often resulting in delayed and inaccurate treatment and unnecessary therapy. Our research focuses on identifying host transcriptomic biomarkers in the blood of children affected by viral and bacterial pneumonia, alongside healthy controls. The main goal is to establish a gene-expression signature enhancing disease diagnosis and management. We conducted an analysis of a total of 192 whole blood samples, comprising 38 controls and 154 viral and bacterial pneumonia patients recruited through the EUCLIDS clinical network. Our investigation identified 5,486 differentially expressed genes (DEGs) when comparing blood RNA from pneumonia patients with healthy controls. Functional enrichment analysis highlighted pathways related to the immune system response, encompassing neutrophil degranulation, humoral immune response, and various inflammatory pathways. In the comparative analysis of gene expression between viral and bacterial pneumonia patients, we identified 272 DEGs. Gene set analysis revealed a significant difference in pathway enrichment for the immune response, contingent on the over-regulation of gene sets in viral or bacterial pneumonias. Furthermore, we identified a 5-transcript host signature specifically designed to distinguish between viral and bacterial pediatric pneumonia (FAM20A, BAG3, TDRD9, MXRA7 and KLF14; AUC: 0.95 [0.88–1.00]), pseudo-validated in a cohort including probable bacterial and viral patients (AUC: 0.87 [0.77–0.97]). This signature holds the potential to enhance the accuracy of previously described general transcript-based signatures for viral and bacterial infections.
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Project description:Microbial Dynamics and Pulmonary Immune Responses in COVID-19 Secondary Bacterial Pneumonia
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Project description:Pneumonia remains the leading cause of death in children under five, but existing diagnostic methods frequently lead to either insufficient or excessive treatments. Our study aims to bridge this gap by identifying host transcriptomic biomarkers in the blood of children with confirmed viral or bacterial pneumonia. Using RNA sequencing, we identified and validated in an independent cohort a 5-transcript signature that accurately differentiates bacterial from viral pneumonia. This signature has considerable potential to improve diagnostic accuracy for pediatric pneumonia, minimizing delays in diagnosis and avoiding unnecessary treatments, with the possibility of significantly impacting clinical practice. a strand specific library preparation was completed using NEBNext® Ultra™ II mRNA kit (NEB) and NEB rRNA/globin depletion probes following manufacturer’s recommendations. Individual libraries were normalized using Qubit, pooled together and diluted. The sequencing was performed using a 150 paired-end configuration in a Novaseq6000 platform. Quality control of raw data was carried out using FastQC, alignment and read counting were performed using STAR, alignment filtering was done with SAMtools and read counting was carried out using FeatureCounts. RNAseq data was processed for batch correction using control samples and COMBAT-Seq package.
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