Isolation and Single-Cell RNA Sequencing of Pancreatic Cells

Different cells were isolated by digesting pancreatic tissue with 1 mg/mL collagenase P, 2 U/mL dispase II, 0.1 mg/mL soybean trypsin inhibitor, and 0.1 mg/mL DNase I in HBSS with Ca²⁺/Mg²⁺. Tissue dissociation was performed using a gentle MACS™ Octo Dissociator at 37 °C for 40 min. Tissue was digested with 0.05% trypsin-EDTA for an additional 5 min at 37 °C and red blood cells were removed with red blood cell lysis buffer. We followed the steps in the manufacturer’s protocol (Chromium Single Cell 3’ GEM, Library & Gel Bead Kit v3, PN-1000075) to load cells onto 10× Chromium Single Cell Controller Chip B (10× Genomics). This was the method used by the authors in the source article to isolate cells [9 (link)]. The GSE188819 dataset was downloaded from the GEO database. Data quality control and preprocessing were performed using the Seurat package (v4.0.2, Rahul Satijaa, Oxford, UK, https://satijalab.org/seurat/, accessed on 1 September 2022). Genes were removed from the red blood cells: Hba1, Hba2, Hbb, Hbd, Hbe1, Hbg1, Hbg2, Hbm, Hbq1, and Hbz. NormalizeData(), FindVariableFeatures(), and ScaleData() were applied to normalize the scRNA-Seq data. The filtered scRNA-Seq datasets of CER and the control sample were integrated using the Seurat anchor-based integration method [10 (link)], based on the expression of the 2000 most variable features of each sample.