Gene expression data from oleacein-treated SH-SY5Y cells. Gene expression data from oleacein-treated SH-SY5Y cells

Gene expression profiling reveals potential effects of Oleacein in promoting neurogenesis and mitigating neuroinflammation in SH-SY5Y cells under normal and lipopolysaccharide (LPS)-induced conditions. We evaluated the neuroprotective effects of oleacein (OC), a rare secoiridoid derivative found in extra virgin olive oil. our goal was to explore the BDNF/TrkB neurotrophic activity of OC and subsequently assess its potential for modulating neuroinflammatory response in vitro using human neuroblastoma cells (SH-SY5Y cells). Overall design: According to the manufacturer's guide, the RNA was extracted using Isogen kit (Nip-pon Gene Co. Ltd., Japan). Then, RNA quantity and quality were determined using the NanoDrop 2000 spectrophotometer (ThermoScientific, USA). DNA microarray analysis was conducted on control, oleacein-treated, LPS induced, and oleacein+LPS treated SH-SY5Y cells using the GeneChip WT PLUS Reagent Kit (ThermoFisher Scientific) and GeneChip™ Hybridization, Wash and Stain Kit (ThermoFisher Scientific) following the manufacturer's instructions. In brief, complementary DNA (cDNA) was synthesized from 100 ng of RNA solutions. cRNA was synthesized from in vitro transcription of cDNA and then purified and reverse transcribed. Finally, single-stranded cDNA (ss-cDNA) was synthesized, purified, fragmented, and labeled following the manufacturer's instructions. Cartridge Array Hybridization was performed using the Clariom S array (Human; ThermoFisher Scientific) on the GeneChip™ Fluidics Station (ThermoFisher Scientific). Scanning was performed using GeneChip Scanner (ThermoFisher Scientific). The raw image data obtained after scanning were analyzed using the Transcriptome Analysis Console (TAC) software (ver. 4.0.2, ThermoFisher Scientific). The raw data were normalized following the signal space transformation robust multi-chip analysis (SST-RMA) algorithm. Further, gene-level analysis was performed using the Limma Bioconductor package. For differential expression analysis, a One-Way ANOVA followed by an empirical Bayes correction was performed. The detected above back-ground (DABG) cutoff was set to 0.05. The positive vs negative area under the curve (AUC) value was set at greater than or equal to 0.7. Finally, genes that passed the filter criteria of p value 2 (in linear space) were considered as differentially expressed genes (DEGs).