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估算用于中国仓鼠卵巢细胞补料分批培养中抗体聚集荧光在线监测的外在染料

Estimating Extrinsic Dyes for Fluorometric Online Monitoring of Antibody Aggregation in CHO Fed-Batch Cultivations.

作者信息

Schwab Karen, Hesse Friedemann

机构信息

Institute of Applied Biotechnology, Biberach University of Applied Science, 77781 Biberach, Germany.

出版信息

Bioengineering (Basel). 2017 Jul 24;4(3):65. doi: 10.3390/bioengineering4030065.

Abstract

Multi-wavelength fluorescence spectroscopy was evaluated in this work as tool for real-time monitoring of antibody aggregation in CHO fed-batch cultivations via partial least square (PLS) modeling. Therefore, we used the extrinsic fluorescence dyes 1-anilinonaphthalene-8-sulfonate (ANS), 4,4'-bis-1-anilinonaphthalene-8-sulfonate (Bis-ANS), or Thioflavin T (ThT) as medium additives. This is a new application area, since these dyes are commonly used for aggregate detection during formulation development. We determined the half maximum inhibitory concentrations of ANS (203 ± 11 µmol·L), Bis-ANS (5 ± 0.5 µmol·L), and ThT (3 ± 0.2 µmol·L), and selected suitable concentrations for this application. The results showed that the emission signals of non-covalent dye antibody aggregate interaction superimposed the fluorescence signals originating from feed medium and cell culture. The fluorescence datasets were subsequently used to build PLS models, and the dye-related elevated fluorescence signals dominated the model calibration. The soft sensors based on ANS and Bis-ANS signals showed high predictability with a low error of prediction (1.7 and 2.3 mg·mL aggregates). In general, the combination of extrinsic dye and used concentration influenced the predictability. Furthermore, the ThT soft sensor indicated that the intrinsic fluorescence of the culture might be sufficient to predict antibody aggregation online.

摘要

在本研究中,通过偏最小二乘法(PLS)建模,对多波长荧光光谱法作为实时监测CHO补料分批培养中抗体聚集的工具进行了评估。因此,我们使用了外在荧光染料1-苯胺基萘-8-磺酸盐(ANS)、4,4'-双-1-苯胺基萘-8-磺酸盐(双ANS)或硫黄素T(ThT)作为培养基添加剂。这是一个新的应用领域,因为这些染料通常用于制剂开发过程中的聚集体检测。我们测定了ANS(203±11 μmol·L)、双ANS(5±0.5 μmol·L)和ThT(3±0.2 μmol·L)的半数最大抑制浓度,并为该应用选择了合适的浓度。结果表明,非共价染料-抗体聚集体相互作用的发射信号叠加了来自补料培养基和细胞培养物的荧光信号。随后,利用荧光数据集建立PLS模型,与染料相关的荧光信号增强主导了模型校准。基于ANS和双ANS信号的软传感器显示出较高的预测能力,预测误差较低(聚集体为1.7和2.3 mg·mL)。一般来说,外在染料与使用浓度的组合会影响预测能力。此外,ThT软传感器表明,培养物的内在荧光可能足以在线预测抗体聚集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d98/5615311/0242eb47fdd3/bioengineering-04-00065-g001.jpg

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