Precision analysis for the determination of steric mass action parameters using eight tobacco host cell proteins.

ABSTRACT

Plants are advantageous as biopharmaceutical manufacturing platforms because they allow the economical and scalable upstream production of proteins, including those requiring post-translational modifications, but do not support the replication of human viruses. However, downstream processing can be more labor-intensive compared to fermenter-based systems because the product is often mixed with abundant host cell proteins (HCPs). Modeling chromatographic separation can minimize the number of process development experiments and thus reduce costs. An important part of such modeling is the sorption isotherm, such as the steric mass action (SMA) model, which describes the multicomponent protein-salt equilibria established in ion-exchange systems. Here we purified ten HCPs, including 2-Cys-peroxiredoxin, from tobacco (Nicotiana tabacum and N. benthamiana). For eight of these HCPs, we obtained sufficient quantities to determine the SMA binding parameters (KSMA and ν) under different production-relevant conditions. We studied the parameters for 2-Cys-peroxiredoxin on Q-Sepharose HP in detail, revealing that pH, resin batch and buffer batch had little influence on KSMA and ν, with coefficients of variation (COVs) less than 0.05 and 0.21, respectively. In contrast, the anion-exchange resins SuperQ-650S, Q-Sepharose FF and QAE-550C led to COVs of 0.69 for KSMA and 0.05 for ν, despite using the same quaternary amine functional group as Q-Sepharose HP. Plant cultivation in summer vs winter resulted in COVs of 0.09 for KSMA and 0.02 for ν, revealing a small impact compared to COVs of 17.15 for KSMA and 0.20 for ν when plants were grown in different settings (climate-controlled phytotron vs greenhouse). We conclude that plant cultivation can substantially affect protein properties and the resulting SMA parameters. Accordingly, plant growth but also protein purification and characterization for chromatography model building should be tightly controlled and well documented.