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首页> 外文期刊>Journal of Biotechnology >Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling
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Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling

机译:使用完整细胞MALDI-ToF质谱指纹图谱和PLS-DA建模对重组哺乳动物细胞系表型进行快速高通量表征,分类和选择

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Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10 L bioreactor model of Lonza's large-scale (up to 20,000 L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10 L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10 L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements
机译:尽管在过去的几十年中,高产重组哺乳动物细胞系的发展取得了许多进展,但由于无法预测大规模(大型)细胞系的表型特征(例如生长或重组蛋白生产力),细胞系的选择和发展往往会减慢体积的生物反应器),使用小规模的早期细胞系构建数据。在这里,我们描述了哺乳动物细胞完整细胞MALDI-ToF质谱指纹图谱方法在细胞系构建过程早期的发展,由此所得的质谱数据用于使用偏最小二乘预测较大培养规模的哺乳动物细胞系的表型。平方判别分析(PLS-DA)模型。使用MALDI-ToF质谱,在细胞系发育的96个深孔板阶段,为单个细胞系生成了质谱指纹图谱库。在Lonza大规模(最多20,000 L)分批补料细胞培养过程的10 L生物反应器模型中评估了这些细胞系的生长和生产力。利用96深孔板阶段的质谱信息和10 L生物反应器规模的表型信息,开发了PLS-DA模型,根据其在MALDI-ToF指纹图谱下的预测,预测了10 L规模未知细胞系的生产力。 96深孔板刻度。该方法为在cGMP生产规模的生物反应器中非常早期预测细胞系性能提供了基础,并且为基于快速完整细胞质谱的测量方法预测其他哺乳动物细胞表型的方法和模型奠定了基础

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