Premium
A framework for real‐time glycosylation monitoring (RT‐GM) in mammalian cell culture
Author(s) -
Tharmalingam Tharmala,
Wu ChaoHsiang,
Callahan Susan,
T. Goudar Chetan
Publication year - 2015
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.25520
Subject(s) - glycosylation , fucosylation , glycan , process (computing) , n linked glycosylation , chemistry , computer science , computational biology , biochemical engineering , biochemistry , biology , glycoprotein , engineering , operating system
Glycosylation is a critical characteristic of biotherapeutics because of its central role in in vivo efficacy. Multiple factors including medium composition and process conditions impact protein glycosylation and characterizing cellular response to these changes is essential to understand the underlying relationships. Current practice typically involves glycosylation characterization at the end of a fed‐batch culture, which in addition to being an aggregate of the process, reflects a bias towards the end of the culture where a majority of the product is made. In an attempt to rigorously characterize the entire time‐course of a fed‐batch culture, a real‐time glycosylation monitoring (RT‐GM) framework was developed. It involves using the micro sequential injection (μSI) system as a sample preparation platform coupled with an ultra‐performance liquid chromatography (UPLC) system for real‐time monitoring of the antibody glycan profile. Automated sampling and sample preparations were performed using the μSI system and this framework was used to study manganese (Mn)‐induced glycosylation changes over the course of a fed‐batch culture. As expected, Mn‐supplemented cultures exhibited higher galactosylation levels compared to control while the fucosylation and mannosylation were consistent for both supplemented and control cultures. Overall, the approach presented in the study allows real time monitoring of glycosylation changes and this information can be rapidly translated into process control and/or process optimization decisions to accelerate process development. Biotechnol. Bioeng. 2015;112: 1146–1154. © 2014 Wiley Periodicals, Inc.