Verapamil treatment of ß-cells
In this study, we investigated the molecular and cellular mechanisms of verapamil treatment on ß-cell function and survival using MIN6 cells. Verapamil's molecular processes were studied using transcriptomic data. MTT, cell count, and flow cytometry assessed cell proliferation, growth, and cycle. MIN6 cell function was assessed by glucose-stimulated insulin release and total insulin content. Seahorse and metabolic stress kits examined metabolic activity and oxygen consumption rate. The protective impact of verapamil on MIN6 cells was evaluated by challenging the verapamil treated cell with streptozotocin, T1D-cytomix, or T2D-cytomix cocktail. Our results demonstrate that verapamil treatment induced higher proliferation of MIN6 cells, altered expression of various proteins and genes, improved insulin secretion in hyperglycemic conditions, increased basal and maximal respiration levels, along with ß-cell survival against streptozotocin, T1D-, or T2D-cytomix-induced toxicity, and rendered a protective effect. Overall design: Min6 cells were cultured in DMEM media with 5.6 mM glucose supplemented with 15% heat-inactivated fetal bovine serum (FBS), 2 mM l-glutamine, 1 mM sodium pyruvate, 10 mM HEPES, 50 µg/mL penicillin, 100 µg/mL streptomycin, and 70 mM ß-mercaptoethanol at 37.0 °C, with 5% CO2. After 24 hours, cells were treated with 50 µM verapamil for another 24 hours. MIN6 cells at a passage of <25 were used in this study. RNA isolation was performed from the verapamil treated and untreated MIN6 cells (12 independent experiments) using the RNeasy kit (Qiagen, Hilden, Germany), following standard protocol. 40 ng of purified RNA was used for whole transcriptome sequencing. Transcriptome libraries were produced using Truseq stranded mRNA kit (Illumina Inc. USA), following the manufacturer's protocol, and were validated and quantified using bioanalyzer (Agilent, California, United States) and qubit fluorometer (Thermofisher Scientific, Massachusetts, United States), respectively. Then paired-end sequencing on Novaseq 6000 system (Illumina Inc. USA) was carried on. The resulting BCL files were concerted to Fastq using the bcl2fastq v.2.20 tool and qualified ty control of Fastq files using FastQC (v0.11.9). Trimmomatic (v0.39) was used for adaptor and quality trimming, and for the removal of extremely short reads. HISAT2 (v2.1.0) was used for data alignment. To enumerate the number of reads that are associated with the genes, htseq-count tool in HTSeq (v 0.9.1) was used. Differential gene expression analysis was conducted using Bioconductor package edgeR, by adopting the default setting.