Evgeny S Ruchko, Zakhar R Starinnov, Marat S Sabirov, Maria B Chernysheva, Arthur A Lee, Vagif Ali Oglu Gasanov, Andrey V Vasiliev
Isolation of pancreatic islets for single-cell RNA sequencing (scRNA-seq) remains technically challenging because enzymatic digestion, mechanical dissociation, and subsequent purification can cause cell loss, aggregation, and processing-induced transcriptional changes. This study aimed to adapt a practical gradient-free alternative for preparing murine pancreatic islets for downstream single-cell transcriptomic analysis while reducing the number of sample-processing steps. The workflow combined intraductal perfusion of the pancreas with 3 mL of a collagenase solution through the common bile duct, controlled enzymatic digestion at 37 °C, performed manual islet selection without density-gradient purification, and achieved gentle dissociation with Accutase and EDTA. DNase I was included in all post-digestion steps to limit cell aggregation. The protocol was evaluated using pancreatic islets from BKS.Cg-Dock7m +/+ Leprdb/J mice, a model of type 2 diabetes. Compared with Ficoll-based purification, the gradient-free protocol provided viable cell yields within a similar range while eliminating density-gradient preparation, an 18 min gradient centrifugation step, two subsequent wash centrifugations, and the associated transfer and dilution steps. The resulting scRNA-seq library showed satisfactory quality-control (QC) characteristics and retained the major endocrine populations, including β-, α-, δ-, and PP cells. The gradient-free sample also showed a lower overall stress-response score and lower expression of several immediate early genes, although heat shock- and endoplasmic reticulum (ER) stress-associated genes displayed heterogeneous patterns. These differences were considered descriptive because only one pooled scRNA-seq library was generated for each workflow. These findings support gradient-free isolation as a possible alternative to Ficoll-based purification for preparing murine pancreatic islets for scRNA-seq analysis.