Production of novel Spike truncations in Chinese hamster ovary cells (preprint)

SARS-CoV-2 Spike is a key protein that mediates viral entry into cells and elicits antibody responses. Its importance in infection, diagnostics, and vaccinations has created a large demand for purified Spike for clinical and research applications. Spike is difficult to express, prompting modifications to the protein and expression platforms to improve yields. Alternatively, Spike receptor binding domain (RBD) is commonly expressed with higher titers, though it has lower sensitivity in serological assays. Here, we improve transient Spike expression in Chinese hamster ovary (CHO) cells. We demonstrate that Spike titers increase significantly over the expression period, maximizing at 14 mg/L at day 7. In comparison, RBD titers peak at 54 mg/L at day 3. Next, we develop 8 Spike truncations (T1-T8) in pursuit of a truncation with high expression and antibody binding. The truncations T1 and T4 express at 130 mg/L and 73 mg/L, respectively, which are higher than our RBD titers. Purified proteins were evaluated for binding to antibodies raised against full-length Spike. T1 has similar sensitivity as Spike against a monoclonal antibody and even outperforms Spike for a polyclonal antibody. These results suggest T1 is a promising Spike alternative for use in various applications.

Development and simulation of fully glycosylated molecular models of ACE2-Fc fusion proteins and their interaction with the SARS-CoV-2 spike protein binding domain (preprint)

We develop fully glycosylated computational models of ACE2-Fc fusion proteins which are promising targets for a COVID-19 therapeutic. These models are tested in their interaction with a fragment of the receptor-binding domain (RBD) of the Spike Protein S of the SARS-CoV-2 virus, via atomistic molecular dynamics simulations. We see that some ACE2 glycans interact with the S fragments, and glycans are influencing the conformation of the ACE2 receptor. Additionally, we optimize algorithms for protein glycosylation modelling in order to expedite future model development. All models and algorithms are openly available.