Meta-analysis of publicly available Chinese hamster ovary (CHO) cell transcriptomic datasets for identifying engineering targets to enhance recombinant protein yields

Transcriptomics has been extensively applied to the investigation of the CHO cell platform for

the production of recombinant biotherapeutic proteins to identify transcripts whose expression

is regulated and correlated to (non)desirable CHO cell attributes. However, there have been

few attempts to analyse the findings across these studies to identify conserved changes and

generic targets for CHO cell platform engineering. Here we have undertaken a meta-analysis

of CHO cell transcriptomic data and report on those genes most frequently identified as

differentially expressed with regard to cell growth (?) and productivity (Qp). By aggregating

differentially expressed genes from publicly available transcriptomic datasets associated with

? and Qp, using a pathway enrichment analysis and combining it with the concordance of

gene expression values, we have identified a refined target gene and pathway list whilst

determining the overlap across CHO transcriptomic studies. We find that only the cell cycle

and lysosome pathways show good concordance. By mapping out the contributing genes we

have constructed a transcriptomic ‘fingerprint’ of a high-performing cell line. This study

provides a starting resource for researchers who want to navigate the complex landscape of

CHO transcriptomics and identify targets to undertake cell engineering for improved

recombinant protein output.