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A rapid method for the differentiation of yeast cells grown under carbon and nitrogen-limited conditions by means of partial least squares discriminant analysis employing infrared micro-spectroscopic data of entire yeast cells

机译:通过使用整个酵母细胞的红外显微数据进行偏最小二乘判别分析快速区分在碳和氮受限条件下生长的酵母细胞

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摘要

This paper shows the ease of application and usefulness of mid-IR measurements for the investigation of orthogonal cell states on the example of the analysis of Pichia pastoris cells. A rapid method for the discrimination of entire yeast cells grown under carbon and nitrogen-limited conditions based on the direct acquisition of mid-IR spectra and partial least squares discriminant analysis (PLS-DA) is described. The obtained PLS-DA model was extensively validated employing two different validation strategies: (i) statistical validation employing a method based on permutation testing and (ii) external validation splitting the available data into two independent sub-sets. The Variable Importance in Projection scores of the PLS-DA model provided deeper insight into the differences between the two investigated states. Hence, we demonstrate the feasibility of a method which uses IR spectra from intact cells that may be employed in a second step as an in-line tool in process development and process control along Quality by Design principles.
机译:本文以巴斯德毕赤酵母细胞分析为例,展示了中红外测量在研究正交细胞状态方面的简便性和实用性。描述了一种直接鉴定中红外光谱和偏最小二乘判别分析(PLS-DA)的快速方法,用于鉴定在碳和氮限制条件下生长的整个酵母细胞。使用两种不同的验证策略对获得的PLS-DA模型进行了广泛验证:(i)使用基于置换测试的方法进行统计验证;(ii)外部验证将可用数据分为两个独立的子集。 PLS-DA模型的投影得分中的变量重要性提供了对这两个调查状态之间差异的更深入的了解。因此,我们证明了使用完整细胞的红外光谱的方法的可行性,该方法可在第二步中用作按质量通过设计原则进行过程开发和过程控制的在线工具。

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