A Comparative Transcriptomics Workflow for Analyzing Microarray Data From CHO Cell Cultures

Microarray-based comparative transcriptomics analysis is a powerful tool to understand therapeutic protein producing mammalian cell lines at the gene expression level. However, an integrated analysis workflow specifically designed for end-to-end analysis of microarray data for CHO cells, the most prevalent host for commercial recombinant protein production, is lacking. To address this gap, an automated data analysis workflow in R that leverages public domain analysis modules is developed to analyze microarray based gene expression data. In addition to testing the global transcriptome differences of CHO cells at different conditions, the workflow identifies differentially expressed genes and pathways with intuitive visualizations as the outputs. The utility of this automated workflow is demonstrated by comparing the transcriptomic profiles of recombinant protein expressing CHO cells with and without a temperature shift. Statistically significant differential expression at the gene, pathway, and global transcriptome levels are identified and visualized. An automated workflow like the one developed in this study will enable rapid translation of CHO culture microarray data into biologically relevant information for mechanism-driven cell line optimization and bioprocess development.