Large scale microarray profiling and coexpression network analysis of CHO cells identifies transcriptional modules associated with growth and productivity.

Weighted gene coexpression network analysis (WGCNA) was utilised to explore Chinese hamster ovary (CHO) cell transcriptome patterns associated with bioprocess relevant phenotypes. The dataset set used in this study consisted of 295 microarrays from 121 individual CHO cultures producing a range of biologics including monoclonal antibodies, fusion proteins and therapeutic factors; non-producing cell lines were also included. Samples were taken from a wide range of process scales and formats that varied in terms of seeding density, temperature, medium, feed medium, culture duration and product type. Cells were sampled for gene expression analysis at various stages of the culture and bioprocess-relevant characteristics including cell density, growth rate, viability, lactate, ammonium and cell specific productivity (Qp) were determined. WGCNA identified six distinct clusters of co-expressed genes, five of which were found to have associations with bioprocess variables. Two coexpression clusters were found to be associated with culture growth rate (1 positive and 1 negative). In addition, associations between a further three coexpression modules and Qp were observed (1 positive and 2 negative). Gene set enrichment analysis (GSEA) identified a number of significant biological processes within coexpressed gene clusters including cell cycle, protein secretion and vesicle transport. In summary, the approach presented in this study provides a novel perspective on the CHO cell transcriptome.