Protein-Specific Signal Peptides for Mammalian Vector Engineering

Expression of recombinant proteins in mammalian cellfactoriesrelies on synthetic assemblies of genetic parts to optimally controlflux through the product biosynthetic pathway. In comparison to othergenetic part-types, there is a relative paucity of characterized signalpeptide components, particularly for mammalian cell contexts. In thisstudy, we describe a toolkit of signal peptide elements, created usingbioinformatics-led and synthetic design approaches, that can be utilizedto enhance production of biopharmaceutical proteins in Chinese hamsterovary cell factories. We demonstrate, for the first time in a mammaliancell context, that machine learning can be used to predict how discretesignal peptide elements will perform when utilized to drive endoplasmicreticulum (ER) translocation of specific single chain protein products.For more complex molecular formats, such as multichain monoclonalantibodies, we describe how a combination of in silico and targeteddesign rule-based in vitro testing can be employed to rapidly identifyproduct-specific signal peptide solutions from minimal screening spaces.The utility of this technology is validated by deriving vector designsthat increase product titers >= 1.8x, compared to standardindustry systems, for a range of products, including a difficult-to-expressmonoclonal antibody. The availability of a vastly expanded toolboxof characterized signal peptide parts, combined with streamlined insilico/in vitro testing processes, will permit efficient expressionvector re-design to maximize titers of both simple and complex proteinproducts.

Automated summary

This study develops a toolkit of signal peptide elements to enhance the production of biopharmaceutical proteins in Chinese hamster ovary cell factories. Machine learning is used to predict the performance of discrete signal peptide elements in driving translocation of specific protein products. In vitro testing combined with in silico design enables the rapid identification of product-specific signal peptide solutions.