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采用多层次方法通过饲料添加剂调节抗体N-糖基化。

Modulating antibody N-glycosylation through feed additives using a multi-tiered approach.

作者信息

Kranjc Jaka, Kramer Lovro, Mikelj Miha, Anderluh Marko, Pišlar Anja, Brinc Matjaž

机构信息

Institute of Pharmacy, Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia.

Cell Line Engineering and Characterization, Technical Research & Development, Novartis Pharmaceutical Manufacturing LLC, Mengeš, Slovenia.

出版信息

Front Bioeng Biotechnol. 2024 Aug 26;12:1448925. doi: 10.3389/fbioe.2024.1448925. eCollection 2024.

Abstract

Glycosylation of recombinant proteins is a post-translational modification that affects multiple physicochemical and biological properties of proteins. As such, it is a critical quality attribute that must be carefully controlled during protein production in the pharmaceutical industry. Glycosylation can be modulated by various conditions, including the composition of production media and feeds. In this study, the N-glycosylation-modulating effects of numerous compounds, including metal enzyme cofactors, enzyme inhibitors, and metabolic intermediates, were evaluated. Chinese hamster ovary cells producing three different IgG antibodies were cultivated in a fed-batch mode. First, a one-factor-at-a-time experiment was performed in 24-well deep well plates to identify the strongest modulators and appropriate concentration ranges. Then, a full response surface experiment was designed to gauge the effects and interactions of the 14 most effective hit compounds in an Ambr 15 bioreactor system. A wide range of glycoform content was achieved, with an up to eight-fold increase in individual glycoforms compared to controls. The resulting model can be used to determine modulator combinations that will yield desired glycoforms in the final product.

摘要

重组蛋白的糖基化是一种翻译后修饰,它会影响蛋白质的多种物理化学和生物学特性。因此,它是制药行业蛋白质生产过程中必须严格控制的关键质量属性。糖基化可受多种条件调节,包括生产培养基和补料的组成。在本研究中,评估了多种化合物(包括金属酶辅因子、酶抑制剂和代谢中间体)对N-糖基化的调节作用。以补料分批模式培养表达三种不同IgG抗体的中国仓鼠卵巢细胞。首先,在24孔深孔板中进行单因素实验,以确定最强的调节剂和合适的浓度范围。然后,设计了一个完整的响应面实验,以评估14种最有效的活性化合物在Ambr 15生物反应器系统中的作用和相互作用。实现了广泛的糖型含量,与对照相比,单个糖型增加了多达八倍。所得模型可用于确定能在最终产品中产生所需糖型的调节剂组合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b135/11381414/21f9818fcaaf/fbioe-12-1448925-g001.jpg

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