Optimizing antibody expression by using the naturally occurring framework diversity in a live bacterial antibody display system.

Rapid identification of residues that influence antibody expression and thermostability is often needed to move promising therapeutics into the clinic. To establish a method that can assess small expression differences, we developed a Bacterial Antibody Display (BAD) system that overcomes previous limitations, enabling the use of full-length formats for antibody and antigen in a live cell setting. We designed a unique library of individual framework variants using natural diversity introduced by somatic hypermutation, and screened half-antibodies for increased expression using BAD. We successfully identify variants that dramatically improve expression yields and in vitro thermostability of two therapeutically relevant antibodies in E. coli and mammalian cells. While we study antibody expression, bacterial display can now be expanded to examine the processes of protein folding and translocation. Additionally, our natural library design strategy could be applied during antibody humanization and library design for in vitro display methods to maintain expression and formulation stability.