scRNA-seq dataset from "Glucose deprivation and identification of TXNIP as an immunometabolic modulator of T cell activation in cancer"

Gene expression profiling analysis of single cell RNA-seq data from MLR, anti-CD3/anti-CD28 treated and paired untreated CD4+ T cells samples under high glucose (11 mM) and low glucose (1 mM) conditions.

For each sample, cells suspensions in culture medium were recovered, washed once with 0.04% BSA in 1X PBS and processed through 10x Cell Multiplexing Oligo Labeling protocol (10x Genomics, USA) according to the manufacturer’s instructions. ~1,600 cells/µl pooled cell suspensions were prepared with equal number of cells per sample: one for MLR samples, one for non-stimulated T cells samples, and one for anti-CD3/anti-CD28-stimulated T cells samples. Libraries were prepared using the 10x Chromium Single-Cell 3’ v3.1 protocol with Feature Barcode (10x Genomics, USA), according to the manufacturer’s instructions. Sequencing was performed on a NovaSeq 6000 sequencer (Illumina, USA).

Cell Ranger (v6.0.1, 10x Genomics Inc) was applied for demultiplexing, reads mapping against the GRCh38 human reference genome, and UMI counting. Seurat package (v4.4.0) was used to generate Seurat objects. Only genes detected in at least 3 cells were kept. Cells with fewer than 200 genes detected or >15% mitochondrial UMI counts were filtered out. Samples were merged in a unique Seurat object then count data normalization and scaling was performed using Seurat with default parameters. The 2000 most highly variable genes were used for Principal Component Analysis (PCA). Harmony (v0.1.1) was applied for batch effect correction then Uniform Manifold Approximation and Projection (UMAP) and clustering using the Louvain algorithm were performed on the harmony reduction. Non-T or -MoDC clusters were removed for further analysis.