A Score-Based Rapid Screening and Network Visualization Method Based on Bioactive Ingredient-Induced Variations in Skin Cell Gene Expression

Bioactive ingredients are compounds, typically derived from natural sources, that provide specific health benefits or perform certain beneficial functions. Although they can play a role in maintaining good health, their effects can vary widely based on a person’s specific genotype and phenotype, leading to situations where certain ingredients induce beneficial responses for some individuals but not others. Herein, we report a method for the rapid discovery of relationships between genes, bioactive ingredients, and physiological effects. First, RNA-Seq was performed after applying 6 plant-derived ingredients to a three-dimensional skin model. After determining expression changes for each ingredient, these changes were ranked and visualized using score-based prediction models. Based on our analysis, we were able to quickly determine and visualize the effect (or lack thereof) of the ingredients on gene expression. Our findings demonstrate the utility of combining RNA-Seq with score-based models and visualizations for screening bioactive ingredients by gene expression, visualizing their impact based on ingredient or physiological effect, and the applicability of this method to any bioactive ingredient for rapid determination of potential ingredients relevant to maintaining health and wellness.