bioRxivBioengineering
Identification of hyperosmotic stress-responsive genes in Chinese hamster ovary cells via genome-wide virus-free CRISPR/Cas9 screening
S. H. Kim, S. Shin, M. Baek, K. Xiong, K. J. l. C. Karottki, H. Hefzi, L. M. Grav, L. E. Pedersen, H. F. Kildegaard, N. E. Lewis, J. S. Lee, G. M. Lee
Abstract
Chinese hamster ovary (CHO) cells are the preferred mammalian host cells for therapeutic protein production that have been extensively engineered to possess the desired attributes for high-yield protein production. However, empirical approaches for identifying novel engineering targets are laborious and time-consuming. Here, we established a genome-wide CRISPR/Cas9 screening platform for CHO-K1 cells with 111,651 guide RNAs (gRNAs) targeting 21,585 genes using a virus-free recombinase-mediated cassette exchange-based gRNA integration method. Using this platform, we performed a positive selection screening under hyperosmotic stress conditions and identified 180 genes whose perturbations conferred resistance to hyperosmotic stress in CHO cells. Functional enrichment analysis identified hyperosmotic stress responsive gene clusters, such as tRNA wobble uridine modification and signaling pathways associated with cell cycle arrest. Furthermore, we validated 32 top-scoring candidates and observed a high rate of hit confirmation, demonstrating the potential of the screening platform. Knockout of the novel target genes, Zfr and Pnp, in monoclonal antibody (mAb)-producing recombinant CHO (rCHO) cells and bispecific antibody (bsAb)-producing rCHO cells enhanced their resistance to hyperosmotic stress, thereby improving mAb and bsAb production. Overall, the collective findings demonstrate the value of the screening platform as a powerful tool to investigate the functions of genes associated with hyperosmotic stress and to discover novel targets for rational cell engineering on a genome-wide scale in CHO cells.
- organism: mouse
- research focus: gene regulatory network inference
- approach: genetic perturbation / CRISPR
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