Elp-ligand based affinity precipitation for protein purification: discovery, design and process development

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Mullerpatan, Akshat, Prasad
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Electronic thesis
Chemical engineering
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Chromatographic separation is the chief purification technique used in the downstream processing of biomolecules today. However, there is a growing need to develop economical and scalable capture strategies to handle the increasing diversity and growing titers of therapeutic proteins. Affinity precipitation has shown potential as a non-chromatographic biological product capture technique. In this work, affinity peptides specific to proteins of interest are combined recombinantly with thermo-responsive elastin-like polypeptides (ELPs) to make peptide-ELP fusions, which selectively purify the target proteins from their fermentation broth by inverse transition cycling (ITC). Peptide-protein pairs of varied affinities were chosen for initial proof of concept studies. Peptide-ELP constructs were created recombinantly and were evaluated for the purification of the respective target proteins. While low affinity peptides were not successful in recovering the corresponding protein, higher affinity peptides such as Flag tag DYKDDDDK and the Streptavidin binding peptide DVEAWLDERVPLVET were indeed successful in the purification and recovery of the corresponding proteins from complex mixtures. Further, the role of multivalency was explored and found to be important in achieving complete recovery of the proteins. These results demonstrated the ability of peptide-ELP fusions to purify proteins provided that the peptides have sufficient affinity for the desired biological product. This approach was then extended to the purification of a therapeutically relevant protein target, P-Adnectin (AdP). Phage display was first carried out to identify affinity peptide candidates and in-solution binding assays of the lead peptides to the target were used to identify the most promising peptide P10. The P10-ELP fusion was cloned, expressed and tested for the purification of AdP. Relevant mutations and modifications of the fluid phase conditions were then carried out to further optimize binding and elutability of the AdP from the P10-ELP construct. The final peptide-ELP construct and elution conditions resulted in the recovery of ~83% of ~90% pure AdP from a highly impure E. coli cell lysate. In a parallel effort, the yeast surface display of camelid single domain antibodies (nanobodies) was carried out to identify high affinity nanobody ligands against AdP. Fluorescence activated cell sorting coupled with yeast display were used to aid in the identification of two promising nanobody candidates. The resulting nanobody-ELP constructs were also shown to exhibit encouraging preliminary results for the selective recovery of AdP from a complex mixture. Three novel phage biopanning strategies were then developed and successfully employed for the discovery of different classes of peptide affinity ligands against Fab fragments. The first approach resulted in an affinity peptide for a specific Fab while the second strategy yielded an affinity peptide with broadly specificity towards three kappa light chain IgG1 Fab fragments. The third strategy produced two peptides which bound a wide range of digested Fab fragments, independent of isotype or subclass. A proof of concept study was also carried out to demonstrate the utility of the affinity peptide in a chromatographic column format for Fab purification. The final phase of this thesis involved a proof of concept study into the continuous affinity precipitation process for monoclonal antibodies using the Z domain of protein A fused to ELP (ELP-Z). This approach employed a combination of static mixers and depth filters for the binding, precipitation, capture and recovery of mAbs at high purity and yield. The work in this thesis sets the stage for the implementation of smart biopolymer-affinity ligands for the capture of biological products (both current and next generation) in a continuous format.
School of Engineering
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Rensselaer Polytechnic Institute, Troy, NY
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