Abstract
During manufacturing batches, Chinese hamster ovary (CHO) cells encounter critical levels of environmental stressors which can significantly reduce cell health and productivity. Therefore, stress tolerance must be considered during selection of a suitable host. In this study, we employ a population-based transcriptomic method, referred to as MemorySeq, and differential gene expression analysis on stress-shocked CHO cells to identify stress responsive biomarkers. These biomarkers exhibit transient and intermediate heritable memory states characteristic of epigenetic switches and transcriptional bursting. Using this workflow, 199 genes were found to exhibit transcriptional variability characteristic of two-state systems with switching that forms four network communities of co-fluctuating genes. These communities were enriched in genes related to the regulation of apoptotic processes, gene expression, and metabolic pathways. Seven genes were identified as promising biomarkers of stress-resistance. Genetic engineering methods may be employed in the future to bias clonal populations toward higher stress tolerance to manufacturing stress.