Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: SARS-CoV-2 intra-host evolution during prolonged infection in an immunocompromised patient

PROVIDER: PRJNA837407 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR19175719_1.fastq.gz	Fastqsanger.gz
	SRR19175719_2.fastq.gz	Fastqsanger.gz
	SRR19175720_1.fastq.gz	Fastqsanger.gz
	SRR19175720_2.fastq.gz	Fastqsanger.gz
	SRR19175721_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 6

Similar Datasets

Project description:Prolonged SARS-CoV-2 Infection in an Immunocompromised Individual

| PRJNA836936 | ENA

Intra-host evolution of SARS-CoV-2 during persistent infection: a case study.

Project description:Intra-host evolution of SARS-CoV-2 during persistent infection: a case study.

| PRJEB45613 | ENA

Comparative Pathogenesis of Three Human and Zoonotic SARS-CoV Strains in Cynomolgus Macaques

Project description:The severe acute respiratory syndrome (SARS) epidemic was characterized by increased pathogenicity in the elderly due to an early exacerbated innate host response. SARS-CoV is a zoonotic pathogen that entered the human population through an intermediate host like the palm civet. To prevent future introductions of zoonotic SARS-CoV strains and subsequent transmission into the human population, heterologous disease models are needed to test the efficacy of vaccines and therapeutics against both late human and zoonotic isolates. Here we show that both human and zoonotic SARS-CoV strains can infect cynomolgus macaques and resulted in radiological as well as histopathological changes similar to those seen in mild human cases. Viral replication was higher in animals infected with a late human phase isolate compared to a zoonotic isolate. Host responses to the three SARS-CoV strains were similar and only apparent early during infection with the majority of genes associated with interferon signalling pathways.This study characterizes critical disease models in the evaluation and licensure of therapeutic strategies against SARS-CoV for human use 4 strains, time course, lungs

2011-08-31 | E-GEOD-23955 | biostudies-arrayexpress

Project description:Emergence of SARS-CoV-2 Spike Mutations during Prolonged Infection in Immunocompromised Hosts

| PRJNA1002100 | ENA

SARS-CoV-2 infection rewires host cell metabolism and is potentially susceptible to mTORC1 inhibition

Project description:Viruses hijack host cell metabolism to acquire the building blocks required for viral replication. Understanding how SARS-CoV-2 alters host cell metabolism could lead to potential treatments for COVID-19, the disease caused by SARS-CoV-2 infection. Here we profile metabolic changes conferred by SARS-CoV-2 infection in kidney epithelial cells and lung air-liquid interface cultures and show that SARS-CoV-2 infection increases glucose carbon entry into the TCA cycle via increased pyruvate carboxylase expression. SARS-CoV-2 also reduces host cell oxidative glutamine metabolism while maintaining reductive carboxylation. Consistent with these changes in host cell metabolism, we show that SARS-CoV-2 increases activity of mTORC1, a master regulator of anabolic metabolism, in cell lines and patient lung stem cell-derived airway epithelial cells. We also show evidence of mTORC1 activation in COVID-19 patient lung tissue. Notably, mTORC1 inhibitors reduce viral replication in kidney epithelial cells and patient-derived lung stem cell cultures. This suggests that targeting mTORC1 could be a useful antiviral strategy for SARS-CoV-2 and treatment strategy for COVID-19 patients, although further studies are required to determine the mechanism of inhibition and potential efficacy in patients.

2021-02-19 | ST001709 | MetabolomicsWorkbench

Absence of host innate immune responses in SARS-CoV-infected ferrets upon subsequent challenge

Project description:To further investigate the underlying mechanisms of severe acute respiratory syndrome (SARS) pathogenesis and evaluate the therapeutic efficacy of potential drugs and vaccines it is necessary to use an animal model that is highly representative of the human condition in terms of respiratory anatomy, physiology and clinical sequelae. The ferret, Mustela putorius furo, supports SARS-CoV replication and displays many of the symptoms and pathological features seen in SARS-CoV-infected humans. We have recently established a SARS-CoV infection-challenge ferret platform for use in evaluating potential therapeutics to treat SARS. The main objective of the current study was to extend our previous results and identify early host immune responses upon infection and determine immune correlates of protection upon challenge with SARS-CoV in ferrets. Keywords: time course This study is a simple time course (58 day) examination of host responses in 35 SARS-CoV (TOR2) infected ferrets with the addition of a challenge inoculation of SARS CoV (TOR2) at day 29 post infection. Three mock-infected ferrets are included as negative controls. Due to the unavailability of ferret microarrays, Affymetrix Canine 2.0 oligonucleotide arrays were chosen following sequence analysis of our ferret cDNA library (~5000 clones) and demonstration of high levels of homology (>80%) between dog and ferret.

2013-05-28 | E-GEOD-11704 | biostudies-arrayexpress

Blood RNA-seq data from individuals during the UK Covid-19 lockdown, spanning sequential weeks from first PCR-confirmed SARS-CoV-2 infection, used to evaluate blood transcriptomic signatures of viral infection and identify host-response biomarkers of early SARS-CoV-2 infection

Project description:Healthcare workers were recruited at St Bartholomew’s Hospital, London, UK in the week of lockdown in the United Kingdom (between 23rd and 31st March 2020). Participants underwent weekly evaluation using a questionnaire and biological sample collection (including serological assays) for up to 16 weeks when attending for work and self-declared as fit to attend work at each visit, with further follow up samples collected at 24 weeks. Blood RNA sequencing data was to be used to identify host-response biomarkers of early SARS-CoV-2 infection, to evaluate existing blood transcriptomic signatures of viral infection, and to describe the underlying biology during SARS-CoV-2 infection. This submission includes a total of 172 blood RNA samples from 99 participants. Of these, 114 samples (including 16 convalescent samples collected 6 months after infection) were obtained from 41 SARS-CoV-2 cases, with the remaining 58 from uninfected controls. Participants with available blood RNA samples who had PCR-confirmed SARS-CoV-2 infection during follow-up were included as ‘cases’. Those without evidence of SARS-CoV-2 infection on nasopharyngeal swabs and who remained seronegative by both Euroimmun anti S1 spike protein and Roche anti nucleocapsid protein throughout follow-up were included as uninfected controls. ‘Cases’ include all available RNA samples, including convalescent samples at week 24 of follow-up for a subset of participants. For uninfected controls, we included baseline samples only. Sample class denotes weekly interval to positive SARS-CoV-2 PCR; non-infected controls (NIC); convalescent samples (Conv)_.

2021-07-07 | E-MTAB-10022 | biostudies-arrayexpress

CRISPR screen of human embryonic stem cell line h-pES10 for the identification of host factors for SARS-COV-2 infection

Project description:To search for host factors regulating SARS-COV-2 infection, we performed a genome-wide loss-of-function CRISPR/Cas9 screen in haploid human ESCs. The regulators were identified by the quantification of enrichment of their mutant clones within a pooled loss-of-function library upon SARS-COV-2 infection.

2023-08-09 | E-MTAB-12505 | biostudies-arrayexpress

RNA-Seq investigating the global landscape of the host molecular response to infection by SARS-CoV-2 variants of concern

Project description:Purpose: RNA-Seq was performed for gene expression analysis following infection of human cells with different VOC depending on the experiment group to investigate changes in the host and viral molecular response. Methods: RNA was extracted from 10^6 cells using the Qiagen RNeasy extraction kit according to the manufacturer's protocol and quantified by nanodrop. Samples were submitted for RNA-Seq to Genewiz (Azenta) for library preparation and subsequent steps. Results: We have identified SARS-CoV-2 VOC-specific differences in RNA expression, including for N, Orf9b, and Orf6. We have also measured ISG expression and proinflammatory gene suppression across the VOC, determining changes in ISG expression and proinflammatory gene suppression during amongst VOC during SARS-CoV-2 evolution. Conclusions: Our study examines changes in the host molecular response to VOC infection to identify changes in gene expression, especially those related to the innate immune response, that have occurred during SARS-CoV-2 evolution.

2023-09-20 | GSE213759 | GEO

Host transcriptional responses to SARS-CoV-2 infection in a human nose organoid model

Project description:As a means to identify host transcriptional responses to SARS-CoV-2 infection, we generated RNA-seq data on the human nose organoid model HNO2043. We sampled HNO204 cells infected with SARS-CoV-2 and Mock control cells at 6hrs, 72hrs, and 6 days post-infection, and we profiled these samples for gene expression. Comparisons of the HNO204 transcriptional response to SARS-CoV-2 in relation to transcriptional responses observed in other models and patient samples would suggest the existence of distinct host responses to SARS-CoV-2 depending on cellular context.

2023-09-28 | GSE234484 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data