Lectin bio-layer interferometry for assessing product quality of Fc- glycosylated immunoglobulin G

Abstract

Glycosylation, as the most prominent posttranslational modification, is recognized as an important quality attribute of monoclonal antibodies affected by various bioprocess parameters and cellular physiology. A method of lectin-based bio-layer interferometry (LBLI) to relatively rank galactosylation and fucosylation levels was developed. For this purpose, Fc-glycosylated immunoglobulin G (IgG) was recombinantly produced with varying bioprocess conditions in 15 L bioreactor and accumulated IgG was harvested. The reliability, the robustness and the applicability of LBLI to different samples has been proven. Data obtained from LC-MS analysis served as reference and were compared to the LBLI results. The introduced method is based on non-fluidic bio-layer interferometry (BLI), which becomes recently a standard tool for determining biomolecular interactions in a label-free, real-time and high-throughput manner. For the intended purpose, biotinylated lectins were immobilized on disposable optical fiber streptavidin (SA) biosensor tips. Aleuria aurantia lectin (AAL) was used to detect the core fucose and Ricinus communis agglutinin 120 (RCA120) to determine galactosylation levels. In our case study it could be shown that fucosylation was not affected by variations in glucose feed concentration and cultivation temperature. However, the galactosylation could be correlated with the ratio of mean specific productivity (q_P ) and ammonium (q_NH4+ ) but was unrelated to the ratio of mean q_P and the specific glucose consumption (q_gluc ). This presented method strengthens the applicability of the BLI platform, which already enables measurement of several product related characteristics, such as product quantity as well as kinetic rates (k_d ,k_on ) and affinity constants (k_D ) analysis.

Keywords: CHO cell culture; bio-layer interferometry; fucosylation; galactosylation; glycosylation.

Figure 1

IgG antibody and N‐glycan structures. Schematic representation of a glycoprotein IgG (mAbs contains only Fc glycosylation). The disulfide bonds stabilizing the tertiary and quaternary protein structure are also shown

Figure 2

(a) Sensorgram of a typical test performance, including baseline steps (A, C), lectin loading (B) and association of reduced immunoglobulin G (D). (b) Dose–response curve of IgG by serial dilution of one reduced sample (run 12), diluted to 15, 7.5, 3.75, and 1.875 μg/mL in sample diluent. RCA120 lectin was immobilized on streptavidin sensor tips prior IgG association. The linear signal curve resulted in an equation of y = 0.0381 × −0.0084 and in a correlation coefficient of 0.9986

Figure 3

(a) The proportion of fucosylated glycoforms determined via LC–MS and the responses of the lectin based BLI (LBLI) assay in nm depicted for all runs. (b) Linear regression analysis of all 13 CHO cell culture fed batch runs performed in 15 L pilot scale. The responses in [nm] of LBLI assay were compared with obtained galactosylated glycoforms in (%) of LC–MS measurements. Dots and error bars represent the mean Rt values and standard deviation of LBLI triplicate measurements, and the corresponding results from a single LC–MS run (without SD). The regression line and its single confidence band (dashed line) are plotted. The linear regression line resulted in the equation of y = 0.0309 × −0.277 and a correlation coefficient of 0.8925

Figure 4

The impact of the ratios q_P to q_gluc (a) and to q_NH4+ (b) on the LBLI response or respectively the galactosylation proportion of the mAb. The regression lines and coefficients are depicted. (b) Regression line depicted was performed without the outlier. The arrow indicates the outlier. The confidence band (dashed line) are plotted. Example trends of process run 12 for (c) glucose concentration and the respective specific rate and (d) ammonium concentration and the respective specific rate