Characterization and prediction of positional 4-hydroxyproline and sulfotyrosine, two post-translational modifications that can occur at substantial levels in CHO cells-expressed biotherapeutics

Oksana Tyshchuk, Christoph Gstöttner, Dennis Funk, Simone Nicolardi, Stefan Frost, Stefan Klostermann, Tim Becker, Elena Jolkver, Felix Schumacher, Claudia Ferrara,

mAbs · 2019 · 26 citations · 39 references

DOIFull text

Open access

Abstract

Biotherapeutics may contain a multitude of different post-translational modifications (PTMs) that need to be assessed and possibly monitored and controlled to ensure reproducible product quality. During early development of biotherapeutics, unexpected PTMs might be prevented by <i>in silico</i> identification and characterization together with further molecular engineering. Mass determinations of a human IgG1 (mAb1) and a bispecific IgG-ligand fusion protein (BsAbA) demonstrated the presence of unusual PTMs resulting in major +80 Da, and +16/+32 Da chain variants, respectively. For mAb1, analytical cation exchange chromatography demonstrated the presence of an acidic peak accounting for 20%. A + 79.957 Da modification was localized within the light chain complementarity-determining region-2 and identified as a sulfation based on accurate mass, isotopic distribution, and a complete neutral loss reaction upon collision-induced dissociation. Top-down ultrahigh resolution MALDI-ISD FT-ICR MS of modified and unmodified Fabs allowed the allocation of the sulfation to a specific Tyr residue. An aspartate in amino-terminal position-3 relative to the affected Tyr was found to play a key role in determining the sulfation. For BsAbA, a + 15.995 Da modification was observed and localized to three specific Pro residues explaining the +16 Da chain A, and +16 Da and +32 Da chain B variants. The BsAbA modifications were verified as 4-hydroxyproline and not 3-hydroxyproline in a tryptic peptide map via co-chromatography with synthetic peptides containing the two isomeric forms. Finally, our approach for an alert system based on in-house <i>in silico</i> predictors is presented. This system is designed to prevent these PTMs by molecular design and engineering during early biotherapeutic development.

References

39