Summary: Transcriptional analysis of SARS-CoV-2 specific CD4 T cells
Overall Design: The objective of this analysis was to determine if there was a transcriptional difference in the CD4 T cell response elicited by SARS-CoV-2 infection in individuals that quickly resolved their infection compared to those individuals with prolonged SARS-CoV-2-associated symptoms
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Growth Protocol: | - |
Treatment Protocol: | Cryopreserved PBMC samples were thawed and resuspended in complete cell culture media at a concentration of 5 × 106 cell/mL and stimulated with 0.5 μg/mL of a SARS-CoV-2 Spike protein peptide pool for 18 h at 37 °C. Spike-reactive CD4+ T cells were identified by expression of the activation markers CD134 and CD69 and isolated by flow cytometric sorting using BD FACSAria II instrument. Cells were sorted directly into 350ul RLT+ buffer supplemented with 1% 2-ME |
Extract Protocol: | RNA isolated from RLT+ buffer using a RNeasy Micro spin column according to the manufacuter's protocol |
Library Construction Protocol: | cDNA was generated using a SMART-Seq HT Kit (TaKaRa, 634455), and the final Illumina-compatible DNA sequencing libraries prepared using an Illumina Nextera XT DNA Library Preparation kit |
Molecule Type: | polyA(+) RNA |
Library Source: | |
Library Layout: | SINGLE |
Library Strand: | - |
Platform: | ILLUMINA |
Instrument Model: | Illumina NextSeq 500 |
Strand-Specific: | Unspecific |
Data Resource | GEN Sample ID | GEN Dataset ID | Project ID | BioProject ID | Sample ID | Sample Name | BioSample ID | Sample Accession | Experiment Accession | Release Date | Submission Date | Update Date | Species | Race | Ethnicity | Age | Age Unit | Gender | Source Name | Tissue | Cell Type | Cell Subtype | Cell Line | Disease | Disease State | Development Stage | Mutation | Phenotype | Case Detail | Control Detail | Growth Protocol | Treatment Protocol | Extract Protocol | Library Construction Protocol | Molecule Type | Library Layout | Strand-Specific | Library Strand | Spike-In | Strategy | Platform | Instrument Model | Cell Number | Reads Number | Gbases | AvgSpotLen1 | AvgSpotLen2 | Uniq Mapping Rate | Multiple Mapping Rate | Coverage Rate |
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