Characterization and comparison of two peptide-tag specific nanobodies for immunoaffinity chromatography

摘要

Affinity chromatography is generally regarded as a powerful tool allowing the single step purification of recombinant proteins with high purity and yields. However, for most protein products, affinity purification methods for industrial applications are not readily available, mainly due to the lack of specific and robust natural counterparts that could function as affinity ligands. In this study, we explored the applicability of nanobody-based peptide-tag immunorecognition systems as a platform for affinity chromatography. Two typical nanobodies (BC2-nb and Syn2-nb) that are capable of recognizing specifically a particular peptide-tag, were prepared through prokaryotic expression and proved to be able to bind with nanomolar affinity to their cognate tag fused to enhanced green fluorescent protein (eGFP). Through an epoxy-based immobilization reaction, the two nanobodies were coupled on a Sepharose CL-6B matrix under the same conditions. The remaining antigen binding activity of the immobilized BC2-nb and Syn2-nb was determined to be 83.1% and 42.9%, yielding the resins with the dynamic binding capacity (DBC) of 21.4 mg/mL and 5.9 mg/mL, respectively. The immobilized affinity ligands exhibited high binding specificity towards their respective target peptides, yielding a product purity above 90% directly from crude bacterial lysates in one single chromatographic step. However, for the both affinity complexes, desorption has been found difficult, and effective recovery of the bound products could be only achieved with competitive elution or after employing harsh conditions such as 10 mM NaOH solution, which will compromise the reuse cycles of the affinity resins. This study shows the potential of nanobody-based affinity chromatography for efficient purification of recombinant proteins especially from complex feedstocks and reveals the primary issues to be addressed to develop a successful application. (C) 2020 Elsevier B.V. All rights reserved.