体液的代谢谱分析与多变量数据分析。
Metabolic profiling of body fluids and multivariate data analysis.
作者信息
Trezzi Jean-Pierre, Jäger Christian, Galozzi Sara, Barkovits Katalin, Marcus Katrin, Mollenhauer Brit, Hiller Karsten
机构信息
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg; Integrated BioBank of Luxembourg, Strassen, Luxembourg.
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
出版信息
MethodsX. 2017 Feb 20;4:95-103. doi: 10.1016/j.mex.2017.02.004. eCollection 2017.
Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC-MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC-MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: •Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process•Small sample volume required•Rapid and cost-effective processing of biological samples•Logistic regression based determination of biomarker signatures for in-depth data analysis.
由于存在诸如预处理延迟和温度等分析前的变化,以及样本中生化过程持续的动态变化,对体液进行代谢组分析具有挑战性。因此,从采集时刻到分析阶段的适当样本处理对于获得高质量样本和可重复结果至关重要。代谢组学分析分为4个主要步骤:1)样本采集,2)代谢物提取,3)数据采集和4)数据分析。在此,我们描述了一种基于气相色谱-质谱联用(GC-MS)的生物基质尤其是体液代谢分析方法。该方法可应用于人类和其他脊椎动物的血清/血浆、唾液和脑脊液(CSF)样本。它涵盖了样本采集、样本预处理、代谢物提取、GC-MS测量以及后续数据分析指南。该方法的优点包括:•考虑到采样过程中可能出现的分析前变化,可获得稳健且可重复的代谢组学结果•所需样本体积小•生物样本处理快速且经济高效•基于逻辑回归确定生物标志物特征以进行深入数据分析。