E-GEOD-33267
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-33267 | ExpressionAtlas | 2020-04-03
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:Proteomics and phosphoproteomics measurments of human a lung epithelial cell line (Calu-3 cells) infected with the novel coronavirus SARS-CoV-2 over a time-course of 4,8 and 12 hours.
2022-07-08 | PXD030395 | Pride
Project description:SARS-CoV-2, the virus responsible for COVID-19, infects both human airway epithelial cells and trigeminal ganglia. We assessed the consequences of SARS-CoV-2 infection on gene expression in Calu-3 cells and in primary Mus musculus trigeminal ganglia cells (mmTG). Here, we provide datasets that include raw reads and mapped reads for the following: 1) mock infected mmTG 48 hrs post infection; 2) SARS-CoV-2 infected mmTG 48 hrs post infection; 3) mock infected Calu-3 cells 24 hrs post infection; 4) SARS-CoV-2 infected Calu-3 cells 24 hrs post infection; 5) mock infected Calu-3 cells 48 hrs post infection; 6) SARS-CoV-2 infected Calu-3 cells 48 hrs post infection.
2024-01-08 | GSE252056 | GEO
Project description:We used two model systems to characterise the changes caused by SARS-CoV-2 using quantitative proteomics. We used primary human epithelial cells differentiated at the air-liquid interface, first describing the relative abundance of proteins found in each major cell type of the epithelium, and then characterised the infection of ciliated cells specifically as these showed the greatest susceptibility to SARS-CoV-2 infection. We also used a lung epithelial cell line, CaLu-3, and compared the infection with B.29 and B.1.1.7 (Alpha) variant over a time-course of infection. In each case, immunostaining for nucleoprotein combined with FACS allowed for the purification of infected cells from uninfected ‘bystander’ cells.
2022-05-26 | PXD034135 | Pride
Project description:We used two model systems to characterise the changes caused by SARS-CoV-2 using quantitative proteomics. We used primary human epithelial cells differentiated at the air-liquid interface, first describing the relative abundance of proteins found in each major cell type of the epithelium, and then characterised the infection of ciliated cells specifically as these showed the greatest susceptibility to SARS-CoV-2 infection. We also used a lung epithelial cell line, CaLu-3, and compared the infection with B.29 and B.1.1.7 (Alpha) variant over a time-course of infection. In each case, immunostaining for nucleoprotein combined with FACS allowed for the purification of infected cells from uninfected ‘bystander’ cells.
2022-11-30 | PXD034101 | Pride
Project description:In the present study, we used data-independent acquisition mass spectrometry (DIA-MS) to analyse the protein expression in Calu-3 cells infected with SARS-CoV and SARS-CoV-2 over the time-course of 24 hours. About 8400 proteins were identified, from which about 90% could be quantified across the experiment. This results in a deep and comprehensive proteome map, which reflects time-dependent protein expression changes during SARS-CoV and SARS-CoV-2 infections and provides deep insights into the virus-specific immunmodulation of human lung cells.
2022-01-20 | PXD024883 | Pride
Project description:Purpose of experiment was to compare transcriptomics of 2B4 cells (clonal derivative of Calu-3 cells) infected with either icSARS CoV or the icSARS deltaORF6 mutant. Calu-3 cells were infected with either icSARS CoV or the icSARS deltaORF6 mutant at MOI of 5.0. Cells samples were collected at 0, 3, 7, 12, 24, 30, 36, 48, 54, 60 or 72h post infection. Each infected sample was done in triplicate. (Triplicates are defined as 3 different wells, plated at the same time using the same cell stock for all replicates.)There are triplicate time-matched mock for each time point from the same cell stock as rest of samples. Culture medium (the same as what the virus stock is in) was used for the mock infections. The NIAID Systems Virology Center
2011-11-01 | E-GEOD-33267 | biostudies-arrayexpress
Project description:Purpose of experiment was to compare transcriptomics of 2B4 cells (clonal derivative of Calu-3 cells) infected with either icSARS CoV or the icSARS deltaORF6 mutant. Calu-3 cells were infected with either icSARS CoV or the cSARS Bat SRBD strain at MOI of 1.0. Cells samples were collected at 0, 7, 12, 24, 30, 36, 48, 54, 60 or 72h post infection. Each infected sample was done in triplicate. (Triplicates are defined as 3 different wells, plated at the same time using the same cell stock for all replicates.)There are triplicate time-matched mock for each time point from the same cell stock as rest of samples. Culture medium (the same as what the virus stock is in) was used for the mock infections. Contributor: The NIAID Systems Virology Center
2012-05-06 | E-GEOD-37827 | biostudies-arrayexpress
Project description:Severe acute respiratory syndrome-associated coronavirus (SARS-CoV) infection causes an immune-mediated disease. We have recently shown that SARS-CoV-induced epithelial Calu-3 cytokines could exacerbate and dampen host inflammatory and T cell responses, respectively, through modulating the functions of macrophages and dendritic cells, thereby suggesting that not only are lung epithelial cells the primary cells of SARS-CoV infection, but they also involve in initiating and orchestrating the host innate and adaptive immunity. Comprehensive evaluation of the complex epithelial signaling to SARS-CoV is, thus, crucial for paving the way to better understand SARS pathogenesis and develop the innovative therapeutics against SARS. Here, based on the microarray-based functional genomics, we reported that 2B4 cells, a clonal derivative of Calu-3 cells, elicited a temporal and spatial activation of nuclear factor (NF)kappaB, activator protein (AP)-1 (ATF2/c-Jun), and interferon regulatory factor (IRF)-3/-7 at 12-, 24-, and 48-hrs post infection (p.i.), respectively, resulting in the activation of many antiviral genes, including interferon (IFN)-β, -λs, SARS-related inflammatory mediators, and various IFN-stimulated genes (ISGs). While elevated responses of IFN-β and IFN-λs were not detected until 48-hrs p.i., as a consequence of a delayed IRF-3/-7 activation, we showed, for the first time, that both types of IFNs exerted previously under-described non-redundant, complementary, and/or synergistic effects on the epithelial defense against SARS-CoV. Collectively, our results highlight the molecular mechanisms of the sequential activation of virus- and IFN-dependent signaling of lung epithelial cells against SARS-CoV and identify novel cellular targets for future studies, aiming at advancing strategies against SARS. DNA microarrays were performed in the Molecular Genomics (MG) Core Facilities at UTMB. The detailed information about the procedures of microarray analysis has been posted on the MG Core Facilities website (genomics@scms.utmb.edu). To characterize the dynamic, spatial, and temporal changes of the gene expression induced by SARS-CoV, confluent 2B4 cells grown in T-75 flasks were infected with SARS-CoV (MOI=0.1) or remained uninfected (as control) for 12, 24, and 48hrs. Because 2B4 cells were also permissive to the productive infection of Dhori virus (DHOV), a member of the Orthomyxoviridae family within the Thogotovirus genus, resulting in robust responses of IFNs and other pro-inflammatory mediators, we also established parallel cultures of DHOV-infected 2B4 cells (MOI=0.1) for the comparative analysis of global gene expression elicited by SARS-CoV- versus DHOV-infected 2B4 cells. To meet the minimal number required for application of statistical algorithms, we performed the study in triplicate at each time point for mock-, SARS-CoV-, and DHOV-infected cultures, yielding a total of 27 arrays. Briefly, supernatants were harvested from differentially treated cultures at 12-, 24-, and 48-hrs p.i. for subsequent analyses of viral yields and cytokine profiling, whereas the cells were subjected to total RNA extraction by using an RNAqueous-4PCR kit and following the protocol recommended by the manufacturer (Ambion, Austin, TX). Purified RNA samples were sent to our core facility for conversion to cDNA, biotin-labeled, and hybridized to 27 Affymetrix Human Genome U133 Plus 2.0 âGene Chipsâ each of which contained 54,675 probe set identifiers representing more than ~47,400 transcripts that identify ~38,500 well-characterized genes, and various internal controls (Affymetrix, Santa Clara, CA). Mock-infected cells were compared to cells infected with SARS-CoV or DHOV at each time point.
2010-02-24 | E-GEOD-17400 | biostudies-arrayexpress
Project description:Differential expression was determined in Calu-3 cells between mock infected and infection with either Human coronavirus EMC and SARS coronavirus at different times post infection. Calu-3 2B4 cells were infected with Human Coronavirus EMC 2012 (HCoV-EMC) or mock infected. Samples were collected 0, 3, 7, 12, 18 and 24 hpi. There are 3 mock and 3 infected replicates for each time point, except for 12 hpi for which there are only 2 infected replicates (one replicate did not pass RNA quality check). There were no mock sampes at 18 hpi, and therefore infected samples at 18 hpi were compared with mocks at 24 hpi. For direct comparison with SARS-CoV infected cells, raw data from HCoV-EMC experiments were quantile normalized together with the SARS-CoV dataset (GEO Series accession number GSE33267).
2013-05-03 | E-GEOD-45042 | biostudies-arrayexpress
Project description:COVID-19 is one of the deadliest respiratory diseases, and its emergence caught the pharmaceutical industry off guard. While vaccines have been rapidly developed, treatment options for infected people remain scarce, and COVID-19 poses a substantial global threat. This study presents a novel workflow to predict robust druggable targets against emerging RNA viruses using metabolic networks and information of the viral structure and its genome sequence. For this purpose, we implemented pymCADRE and PREDICATE to create tissue-specific metabolic models, construct viral biomass functions and predict host-based antiviral targets from more than one genome. We observed that pymCADRE reduces the computational time of flux variability analysis for internal optimizations. We applied these tools to create a new metabolic network of primary bronchial epithelial cells infected with SARS-CoV-2 and identified enzymatic reactions with inhibitory effects. The most promising reported targets were from the purine metabolism, while targeting the pyrimidine and carbohydrate metabolisms seemed to be promising approaches to enhance viral inhibition. Finally, we computationally tested the robustness of our targets in all known variants of concern, verifying our targets’ inhibitory effects. Since laboratory tests are time-consuming and involve complex readouts to track processes, our workflow focuses on metabolic fluxes within infected cells and is applicable for rapid hypothesis-driven identification of potentially exploitable antivirals concerning various viruses and host cell types.
Availability: https://github.com/draeger-lab/pymCADRE/.
2024-04-18 | MODEL2202240001 | BioModels