Technological watch

Multi?lipase gene knockdown in Chinese hamster ovary cells using artificial microRNAs to reduce host cell protein mediated polysorbate degradation

In a proof?of?concept study Weiss and coworkers designed artificial microRNAs (amiRNAs) and applied them in Chinese hamster ovary cell lines targeting polysorbate degrading host cell proteins. They proved functionality of amiRNAs on protein level and successfully reduced polysorbate degradation in cell supernatant. With their work they provide an additional tool for cell line engineering, which might be used beyond the reduction of polysorbate degrading host cell proteins.A large number of companies observe polysorbate (PS) degradation and associated (sub?)visible particle formation in biological drug formulations, which compromise the stability of the drug product, ultimately posing a risk toward delivering innovative medicines to patients. The main culprits of PS degradation are hydrolytic host cell proteins (HCPs) originating from the production cell lines, which are mostly Chinese hamster ovary (CHO) cell derived. Here, a small portion of particularly difficult?to?remove HCPs—mainly lipases—cause hydrolytic cleavage of PS resulting in the accumulation of free fatty acid aggregates/particles. One possible mitigation strategy is the removal of such critical HCPs in the production cell line. Multigene regulation can be achieved via microRNAs (miRNAs) thereby serving as a smart tool to reduce the expression of different target genes using a single miRNA. To enable a tailored gene regulation of multiple specific target lipases self?designed and non?naturally occurring artificial miRNAs (amiRNA) can be designed. Based on micro?conserved regions in the mRNA sequence of two sets of target HCPs, we provide a proof?of?concept for a simultaneous multi?lipase knockdown in CHO cells using single amiRNAs. By this, we were not only able to reduce PS degradation but laid the foundation to expand this tool to other areas of cell line phenotype engineering.

Publication date: 25/09/2023



This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.