{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Agnes Bonifacius"],"organism":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15718"],"description":["CD19-CAR-T cells were generated from human primary CD3+ T cells of three donors in presence or absence of vitamin C. RNA was isolated after 24h of co-culture with Nalm-6 cells. Details of experimental design can be found in the M&M section of the manuscript."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Sample Treatment - S01: CD19 CAR T cells pre exposure to CD19+ B-LCLs. HTO capture antibodies were used to allow discrimination between CD19 CAR T cells generated in presence or absence of vitamin C, obtained in three independent experiments (donors). HTO1: donor 1, 0 µM vitamin C HTO2: donor 1, 50 µM vitamin C HTO3: donor 2, 0 µM vitamin C HTO4: donor 2, 50 µM vitamin C HTO5: donor 3, 0 µM vitamin C HTO6: donor 3, 50 µM vitamin C  S02: CD19 CAR T cells post exposure to CD19+ B-LCLs. HTO capture antibodies were used to allow discrimination between CD19 CAR T cells generated in presence or absence of vitamin C, obtained in three independent experiments (donors). HTO1: donor 1, 0 µM vitamin C HTO2: donor 1, 50 µM vitamin C HTO3: donor 2, 0 µM vitamin C HTO4: donor 2, 50 µM vitamin C HTO5: donor 3, 0 µM vitamin C HTO6: donor 3, 50 µM vitamin C","Sample Collection - CD19-CAR-T cells were generated from human primary CD3+ T cells of three donors in presence or absence of vitamin C. Viable CD3+ T cells were sorted after 24h of exposure to CD19+ B-LCLs.","Library Construction - Library preparation for single cell mRNA-Seq analysis was performed according to the Chromium NextGEM Single Cell 5ʹ Reagent Kits v2 CellSurfaceProtein User Guide (Manual Part Number CG000330 Rev E; 10x Genomics). According to the protocol a given excess (100%) of cells was loaded to the 10x controller. Fragment length distribution of generated libraries was monitored using ‘Bioanalyzer High Sensitivity DNA Assay’ (5067-4626; Agilent Technologies). Quantification of libraries was performed by use of the ‘Qubit® dsDNA HS Assay Kit’ (Q32854; ThermoFisher Scientific).","Nucleic Acid Extraction - Sorted cells were subjected to the 10x pipeline. More details see \\\"nucleid acid library construction protocol\\\".","Sequencing - Generated mRNA expression library and feature barcode library were pooled (with molar proportions corresponding to 45.5% and 4.5% of sequencing run capacity), denatured with NaOH, and were finally diluted to 1.8pM according to the ‘Denature and Dilute Libraries Guide’ (Document # 15048776 v02; Illumina). 1.3 ml of denatured pool (including 1% PhiX) was sequenced on an Illumina NextSeq550 sequencer using one high output flowcell for 75 cycles and 400 million clusters (#20024906; Illumina). Sequencing was performed according to the following settings: 28bp as sequence read 1; 56bp as sequence read 2; 8bp as index read 1 and no index read 2."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","Processed Data","MAGE-TAB Files"],"data_protocol":["Sequence Alignment - The 10x Genomics CellRanger analysis pipeline set (v7.2.0) was used with default parameters. Briefly, BCL files were demultiplexed into FASTQ files by cellranger mkfastq using the respective sample sheet with utilized 10X barcodes. The cellranger count pipeline was used to align read data to the reference genome provided by 10X Genomics (Human reference dataset refdata-gex-GRCh38-2020-A), counting aligned reads per gene and feature barcode, and calculating clustering and summary statistics.","Data Transformation - Outputs from cellranger count of all samples were aggregated, normalized to the same sequencing depth, and then the feature-barcode matrices was recomputed by cellranger aggr. Simultaneously, feature barcoding data was processed during the cellranger count step with a feature reference build according to the specification of TotalSeq™-C antibodies. The output from cellranger count was demultiplexed to retrieve values for each previously pooled sample. Demultiplexing with hashtag oligos was performed using a Seurat (v. 4.1.1) based workflow developed in a collaboration of Dresden-concept Genome Center (TU Dresden) and Research Core Unit Genomics (Hannover Medical School) (https://github.com/ktrns/scrnaseq). Briefly, the workflow (conducted via R version 4.2.1) log-normalized and clustered the HTO counts, classified cells based on normalised HTO data, removed HTO doublet or negative cells, and generated demultiplexed data. Finally, the Loupe Cell Browser (10x Genomics) was utilized to view and revise annotated clusters, based on the implemented tSNE or UMAP algorithms."],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["NextSeq 550"],"study_type":["RNA-seq of coding RNA from single cells"],"species":["Homo sapiens"],"pubmed_authors":["Agnes Bonifacius"],"additional_accession":[]},"is_claimable":false,"name":"scRNAseq of CD19-CAR-T cells generated in presence or absence of vitamin C","description":"CD19-CAR-T cells were generated from human primary CD3+ T cells of three donors in presence or absence of vitamin C. RNA was isolated after 24h of co-culture with Nalm-6 cells. Details of experimental design can be found in the M&M section of the manuscript.","dates":{"release":"2025-11-18T00:00:00Z","modification":"2026-05-27T15:44:22.01Z","creation":"2025-10-14T22:38:18.656Z"},"accession":"E-MTAB-15718","cross_references":{"ENA":["ERP182169"],"EFO":["EFO_0002944","EFO_0004170","EFO_0005684","EFO_0004917","EFO_0005518","EFO_0003816","EFO_0004184","EFO_0003969"]}}