Covid metagenomics
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB57062 | ENA |
REPOSITORIES: ENA
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Project description:Analysis of diversity, co-pathogens, and metagenomics of COVID-19 patients
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Project description:We used total RNA of nasopharyngeal swabs from COVID-19 patients to identify their gene expression profile. Multiple biological process were significantly enriched in either asymptomatic or mildly symptomatic patients. These significantly expressed genes were suggested to contribute to the severity of the disease. We also performed metagenomics analysis to identify differences in the microbiome profile of the two groups of patients.
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Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
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Project description:The Virochip microarray (version 4.0) was used to detect viruses in patients from North America with unexplained influenza-like illness at the onset of the 2009 H1N1 pandemic. We used metagenomics-based technologies (the Virochip microarray) and deep sequencing to analyze nasal swab samples from individuals with 2009 H1N1 infection. This Series includes the Virochip microarray data only.
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Project description:Red blood cells (RBC) depleted whole blood from COVID-19 patients and controls was harvested and processed in order to performed 10X single cell RNA-seq. For COVID-19 patients 2 samples 10 days a part were analyzed.
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Project description:Antibiotic resistance investigation in wastewater of COVID-19 specialty hospital using metagenomics
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Project description:The causative organism, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibits a wide spectrum of clinical manifestations in disease-ridden patients. Differences in the severity of COVID-19 ranges from asymptomatic infections and mild cases to the severe form, leading to acute respiratory distress syndrome (ARDS) and multiorgan failure with poor survival. MiRNAs can regulate various cellular processes, including proliferation, apoptosis, and differentiation, by binding to the 3′UTR of target mRNAs inducing their degradation, thus serving a fundamental role in post-transcriptional repression. Alterations of miRNA levels in the blood have been described in multiple inflammatory and infectious diseases, including SARS-related coronaviruses. We used microarrays to delineate the miRNAs and snoRNAs signature in the peripheral blood of severe COVID-19 cases (n=9), as compared to mild (n=10) and asymptomatic (n=10) patients, and identified differentially expressed transcripts in severe versus asymptomatic, and others in severe versus mild COVID-19 cases. A cohort of 29 male age-matched patients were selected. All patients were previously diagnosed with COVID-19 using TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Waltham, Massachusetts), or Cobas SARS-CoV-2 Test (Roche Diagnostics, Rotkreuz, Switzerland), with a CT value < 30. Additional criterion for selection was age between 35 and 75 years. Participants were grouped into severe, mild and asymptomatic. Classifying severe cases was based on requirement of high-flow oxygen support and ICU admission (n=9). Whereas mild patients were identified based on symptoms and positive radiographic findings with pulmonary involvement (n=10). Patients with no clinical presentation were labelled as asymptomatic cases (n=10).
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Project description:The goal of the experiment was to determine whether monocytes from Alzheimer's disease patients with covid had differentially expressed genes when compared to health individuals.
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