Unknown,Transcriptomics,Genomics,Proteomics

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Transcriptional profiling of activated CD4+ memory T cells exposed to anti-TNF and recombinant human TNF-alpha in vitro

ABSTRACT: We performed an RNA-seq analysis on FACS-sorted CD4+ memory T cells (Tmem, CD4+CD25-CD45RA-) stimulated in vitro with anti-CD3/CD28 coated beads (1:5), IL-2 (100 U/mL) in the presence of a TNF-alpha inhibitor (Etanercept, ETN, 5 Î¼g/mL) or recombinant human TNF-alpha (rhTNF-alpha, 50 ng/mL) treatment. The cells were cultured for three days at 37Â°C and 5% CO2. On day three Tmem were lysed (Buffer RLT supplemented with DTT, QIAGEN) and RNA extraction was performed (RNeasy Plus Micro kit), followed by sample preparation with TruSeq (polyA) mRNA kits (Illumina), RNA sequencing (carried out by an Illumina HiSeq2500), and the alignment of trimmed fastQ files to GRCh38 human reference genome. We also performed a Quality control (QC). This was done using the tool FastQC FastQC/0.11.3-Java-1.7.0_80. QC metrics were calculated for the aligned reads using Picard-tools picard/1.130-Java-1.7.0_80, CollectRnaSeqMetrics, MarkDuplicates, CollectInsertSize-Metrics and SAMtools/1.2-foss-2015b flagstat. Finally, we carried out a Differential expression gene (DEG) analysis using DESeq2, in order to evaluate the impact of ETN and rhTNF-alpha on Transcriptome profiling of stimulated CD4+ Tmem. Principal Component Analysis (PCA) was carried out to visualise the samples given their entire transcriptome and any remaining batch effects.

INSTRUMENT(S): Illumina HiSeq 2500

ORGANISM(S): Homo sapiens

SUBMITTER: Hans Koenen

PROVIDER: E-MTAB-5622 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:RNA-seq analysis was performed to understand the role of type I IFN response during SARS CoV-2 infection using transgenic mice. Each sample was collected from an individual C57BL/6J mouse. The total RNA was extracted from uninfected and SARS-CoV-2 infected mice lung tissue using RNeasy mini kit (QIAGEN #74104). The quantity of RNA was determined using Qubit RNA assay kit with Qubit 4.0 and the quality of RNA was tested using agarose gel electrophoresis and High Sensitivity Tape station Kit (Agilent 2200, #5067-5576, #5067-5577 and #5067-5578). After assessing the quality of RNA, ~900 ng of total RNA was taken for library preparation using NEBNext®Ultra™ II Directional RNA Library kit for Illumina (# E7760L) and NEBNext Poly (A) mRNA Magnetic Isolation Module (# E7490L) as per manufacturer's protocol. The prepared library was quantified using Qubit dsDNA assay kit (Invitrogen, Q32851) followed by quality check (QC) and fragment size distribution using a High Sensitivity Tape station Kit (Agilent 2200, #5067-5584 and #5067-5585). The library was sequenced using the HiSeq 4000 Illumina platform. The paired-end (PE) reads quality checks for each sample were carried out using FastQC v.0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The adapter sequence was trimmed using the BBDuk version 37.58 version 37.58 and the alignment was performed using STAR v.2.5.3a with default parameters with human hg38 genome build, gencode v21 gtf 9GRCh38) from the gencode. The duplicates were discarded using Picard-2.9.4 (https://broadinstitute.github.io/picard/) from the aligned bam files and read counts were generated using featureCount v.1.5.3 from subread-1.5.3 package (https://bioinf.wehi.edu.au/) with Q = 10 for mapping quality. The count files were used as input for downstream differential gene expression analysis with DESeq2 version 1.14.1 9. The genes with read counts of ≤ 10 in any comparison were discarded followed by count transformation and statistical analysis using DESeq “R”. The “P” value were adjusted using the Benjamini and Hochberg multiple testing correction and the differentially expressed genes were identified (fold change of ≥1.5, P-value < 0.05). A unified non-redundant gene list was made for different comparisons and subjected to gene ontology (GO) analysis using the reactome database (https://reactome.org/). The top pathways (p < 0.05) were used for generating heat maps using Complexheatmap (Version 2.0.0) through unsupervised hierarchical clustering. The expression clusters were annotated based on enriched GO terms. Normalized gene expression was used to generate the boxplots with a median depicting the trends in the expression across the different conditions using ggplot2 [version 3.3.5]. The pathways analysis was performed using Metascape database (https://metascape.org/gp/index.html#/main/step1). The top pathways (p < 0.05) were taken for constructing bubble plots using ggplot2 [version 3.3.5].

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Transcriptional profiling of activated CD4+ memory T cells exposed to anti-TNF and recombinant human TNF-alpha in vitro

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