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Accession IconSRP136410

Comparison of young and aged mouse CD8 TN, TVM and TMEM cells directly ex vivo and after polyclonal stimulation

Organism Icon Mus musculus
Sample Icon 25 Downloadable Samples
Technology Badge IconIllumina HiSeq 2500

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Description
The overall study (Quinn et al. Cell Reports, 2018) aimed to understand why CD8 virtual memory T (TVM) cells become markedly less proliferative in response to TCR-driven signals with increasing age, whereas CD8 true naive (TN) cells maintain their proliferative capacity. Age-associated decreases in primary CD8+ T cell responses occur, in part, due to direct effects on naïve CD8++ T cells to reduce intrinsic functionality, but the precise nature of this defect remains undefined. Ageing also causes accumulation of antigen-naïve but semi-differentiated “virtual memory” (TVM) cells but their contribution to age-related functional decline is unclear. Here, we show that TVM cells are poorly proliferative in aged mice and humans, despite being highly proliferative in young individuals, while conventional naïve T cells (TN cells) retain proliferative capacity in both aged mice and humans. Adoptive transfer experiments in mice illustrated that naïve CD8 T cells can acquire a proliferative defect imposed by the aged environment but age-related proliferative dysfunction could not be rescued by a young environment. Molecular analyses demonstrate that aged TVM cells exhibit a profile consistent with senescence, marking the first description of senescence in an antigenically naïve T cell population. Overall design: In the RNA-Seq analysis uploaded here, we have sorted TN cells (CD44lo), TVM cells (CD49dlo CD44hi) and CD8 conventional memory T (TMEM) (CD49dhi CD44hi) cells from naive young mice (3 months old) or aged mice (18 months old). To sort enough cells of each type, we pooled 4 mice, so each replicate represents a pooled sample of 4 mice. Each replicate was split in half, with half the sample frozen in TRIzol immediately for our directly ex vivo or "unstim" sample and the other half of the sample stimulated with plate-bound anti-CD3 (10ug/mL), anti-CD8a (10ug/mL) and antiCD11a (5 ug/mL) and soluble recombinant human IL-2 (10U/mL) for 5 hours, before being frozen in TRIzol as our stimulated or "stim" samples. We therefore collected 2 replicates for each cell subsets (designated "1" and "2") and the "unstim" and "stim" samples are matched. Altogether, we had 24 samples (young (Y) and aged (A); replicate 1 and replicate 2, with cells pooled from 4 mice in each replicate; TN, TVM and TMEM cells; unstim and stim match across each replicate). Due to lane capacity limits for sequencing, we processed these samples for RNA and sequencing in two batches (Batch 1- Y1_Tn_Unstim, Y1_Tvm_Unstim, Y1_Tmem_Unstim, Y1_Tn_Stim, Y1_Tvm_Stim, Y1_Tmem_Stim, A1_Tn_Stim, A1_Tvm_Stim, A1_Tmem_Stim, A2_Tn_Stim, A2_Tvm_Stim, A2_Tmem_Stim. Batch 2- Y2_Tn_Unstim, Y2_Tvm_Unstim, Y2_Tmem_Unstim, Y2_Tn_Stim, Y2_Tvm_Stim, Y2_Tmem_Stim, A1_Tn_Unstim, A1_Tvm_Unstim, A1_Tmem_Unstim, A2_Tn_Unstim, A2_Tvm_Unstim, A2_Tmem_Unstim). Of note, in Batch 2 we ran a duplicate of Y1_Tn_Unstim (Y1_Tn_Unstim_norm) to test for any batch effect, but none was observed. Extracted RNA was treated with recombinant DNAse I (Roche) according to the manufacturer's instructions, purified using the RNeasy MinElute Cleanup columns (Qiagen) and analysed for RNA quality using the RNA 6000 Nano kit (Agilent) on an Agilent 2100 Bioanalyzer. Samples were prepared with the Illumina TruSeq RNA v2 sample preparation protocol (cDNA synthesis, adapter ligation, PCR amplification) (Illumina) and run using 100 bp paired end sequencing on an Illumina Hi-Seq. Adapters were trimmed with Trim Galore and trimmed reads were aligned to mm10 genome with TopHat2 version 2.1.1 (Kim et al., 2013) keeping the strand information. Only concordantly aligned read pairs were retained, duplicate fragments were removed using MarkDuplicates from Picard tools and read pairs with mapping quality less than 5 were discarded. To generate a counts matrix, retained read pairs were assigned to genes using featureCounts function (Liao et al., 2014) from Bioconductor Rsubread package taking into account strand information.
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25
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