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

生物量(生态学) 作文(语言) 质谱法 中国仓鼠卵巢细胞 化学 色谱法 生物化学 生物 生态学 哲学 语言学 受体
作者
Diana Széliová,Harald Schoeny,Špela Knez,Christina Troyer,Cristina Coman,Evelyn Rampler,Gunda Koellensperger,Robert Ahrends,Stephan Hann,Nicole Borth,Jürgen Zanghellini,David E. Ruckerbauer
出处
期刊:Methods in molecular biology [Springer Science+Business Media]
卷期号:: 119-160 被引量:7
标识
DOI:10.1007/978-1-0716-0159-4_7
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
源源完成签到 ,获得积分10
刚刚
害羞外套发布了新的文献求助10
1秒前
1秒前
1秒前
程程发布了新的文献求助10
2秒前
充电宝应助一路向南采纳,获得10
2秒前
4秒前
科研小白完成签到 ,获得积分10
4秒前
浮游应助emilia采纳,获得10
4秒前
5秒前
浮游应助Chara_kara采纳,获得10
5秒前
6秒前
hhgcc应助聪慧的如彤采纳,获得20
7秒前
酷波er应助Colinlau采纳,获得10
7秒前
Rina完成签到,获得积分10
8秒前
8秒前
机智的大侠完成签到 ,获得积分10
8秒前
8秒前
Cheng发布了新的文献求助10
9秒前
luckyblue发布了新的文献求助10
10秒前
Jasper应助tangtang采纳,获得10
10秒前
天天快乐应助芬达采纳,获得10
10秒前
zuoyanwin完成签到,获得积分10
11秒前
heyi发布了新的文献求助10
11秒前
11秒前
11秒前
xzzt完成签到 ,获得积分10
12秒前
积极盼山发布了新的文献求助10
12秒前
精明幻露完成签到,获得积分10
13秒前
励志小薛发布了新的文献求助10
13秒前
JLAlpaca发布了新的文献求助10
13秒前
利子完成签到 ,获得积分10
13秒前
suliu完成签到,获得积分20
13秒前
小陶子完成签到,获得积分10
14秒前
而发的完成签到,获得积分10
14秒前
陈瑞完成签到,获得积分10
15秒前
光亮天蓉发布了新的文献求助10
15秒前
16秒前
Twilight完成签到,获得积分20
16秒前
菜宝儿完成签到,获得积分10
17秒前
高分求助中
Pipeline and riser loss of containment 2001 - 2020 (PARLOC 2020) 1000
哈工大泛函分析教案课件、“72小时速成泛函分析:从入门到入土.PDF”等 660
Comparing natural with chemical additive production 500
The Leucovorin Guide for Parents: Understanding Autism’s Folate 500
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 500
A Manual for the Identification of Plant Seeds and Fruits : Second revised edition 500
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.) 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5216056
求助须知:如何正确求助?哪些是违规求助? 4391027
关于积分的说明 13671418
捐赠科研通 4253032
什么是DOI,文献DOI怎么找? 2333551
邀请新用户注册赠送积分活动 1331132
关于科研通互助平台的介绍 1284932