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用于精确量化哺乳动物细胞总生物量组成的稳健分析方法。

Robust Analytical Methods for the Accurate Quantification of the Total Biomass Composition of Mammalian Cells.

作者信息

Széliová Diana, Schoeny Harald, Knez Špela, Troyer Christina, Coman Cristina, Rampler Evelyn, Koellensperger Gunda, Ahrends Robert, Hann Stephen, Borth Nicole, Zanghellini Jürgen, Ruckerbauer David E

机构信息

Austrian Centre of Industrial Biotechnology, Vienna, Austria.

University of Natural Resources and Life Sciences, Vienna, Austria.

出版信息

Methods Mol Biol. 2020;2088:119-160. doi: 10.1007/978-1-0716-0159-4_7.

DOI:10.1007/978-1-0716-0159-4_7
PMID:31893373
Abstract

Biomass composition is an important input for genome-scale metabolic models and has a big impact on their predictive capabilities. However, researchers often rely on generic data for biomass composition, e.g. collected from similar organisms. This leads to inaccurate predictions, because biomass composition varies between different cell lines, conditions, and growth phases. In this chapter we present protocols for the determination of the biomass composition of Chinese Hamster Ovary (CHO) cells. These methods can easily be adapted to other types of mammalian cells. The protocols include the quantification of cell dry mass and of the main biomass components, namely protein, lipid, DNA, RNA, and carbohydrates. Cell dry mass is determined gravimetrically by weighing a defined number of cells. Amino acid composition and protein content are measured by gas chromatography mass spectrometry. Lipids are quantified by shotgun mass spectrometry, which provides quantities for the different lipid classes and also the distribution of fatty acids. RNA is purified and then quantified spectrophotometrically. The methods for DNA and carbohydrates are simple fluorometric and colorimetric assays adapted to a 96-well plate format. To ensure quantitative results, internal standards or spike-in controls are used in all methods, e.g. to account for possible matrix effects or loss of material. Finally, the last section provides a guide on how to convert the measured data into biomass equations, which can then be integrated into a metabolic model.

摘要

生物质组成是基因组规模代谢模型的重要输入内容,对其预测能力有重大影响。然而,研究人员常常依赖通用数据来获取生物质组成,例如从相似生物体收集的数据。这会导致预测不准确,因为不同细胞系、条件和生长阶段的生物质组成存在差异。在本章中,我们介绍了测定中国仓鼠卵巢(CHO)细胞生物质组成的实验方案。这些方法可轻松适用于其他类型的哺乳动物细胞。实验方案包括细胞干重以及主要生物质成分(即蛋白质、脂质、DNA、RNA和碳水化合物)的定量。通过称量一定数量的细胞,采用重量法测定细胞干重。通过气相色谱质谱法测量氨基酸组成和蛋白质含量。采用鸟枪法质谱法定量脂质,该方法可提供不同脂质类别的数量以及脂肪酸的分布情况。纯化RNA后,采用分光光度法进行定量。DNA和碳水化合物的测定方法是适用于96孔板形式的简单荧光测定法和比色测定法。为确保获得定量结果,所有方法均使用内标或加标对照,例如以考虑可能的基质效应或物质损失。最后,最后一部分提供了有关如何将测量数据转换为生物质方程的指南,然后可将其整合到代谢模型中。

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