Integration of GC–MS and LC–MS for untargeted metabolomics profiling

代谢组学 代谢物 化学 代谢组 色谱法 生物流体 气相色谱-质谱法 代谢物分析 计算生物学 质谱法 生物化学 生物
作者
Özge Cansın Zeki,Cemil Can Eylem,Tuba Reçber,Sedef Kır,Emirhan Nemutlu
出处
期刊:Journal of Pharmaceutical and Biomedical Analysis [Elsevier BV]
卷期号:190: 113509-113509 被引量:316
标识
DOI:10.1016/j.jpba.2020.113509
摘要

Recently, metabolomics analyses have become increasingly common in the general scientific community as it is applied in several researches relating to diseases diagnosis. Identification and quantification of small molecules belonging to metabolism in biological systems have an important role in diagnosis of diseases. The combination of chromatography with mass spectrometry is used for the accurate and reproducible analysis of hundreds to thousands of metabolites in biological fluids or tissue samples. The number of metabolites that can be identified in biological fluids or tissue varies according to the gas (GC) or liquid (LC) chromatographic techniques used. The cover of these chromatographic techniques also differs from each other based on the metabolite group (polar, lipids, organic acid etc.). Consequently, some of the metabolites can only be analyzed using either GC or LC. However, more than one metabolite or metabolite group may be found altered in a particular disease. Thus, in order to find these alterations, metabolomics analyses that cover a wide range of metabolite groups are usually applied. In this regard, GC–MS and LC–MS techniques are mostly used together to identify completely all the altered metabolites during disease diagnosis. Using these combined techniques also allows identification of metabolite(s) with significantly altered phenotype. This review sheds light on metabolomics studies involving the simultaneous use of GC–MS and LC–MS. The review also discusses the coverage, sample preparation, data acquisition and data preprocessing for untargeted metabolomics studies. Moreover, the advantages and disadvantages of these methods were also evaluated. Finally, precautions and suggestions on how to perform metabolomics studies in an accurate, precise, complete and unbiased way were also outlined.
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
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
tenacity发布了新的文献求助20
刚刚
彭于晏应助混子king采纳,获得10
1秒前
orixero应助执着傲蕾采纳,获得10
2秒前
2秒前
小马甲应助challote采纳,获得10
3秒前
6秒前
6秒前
9秒前
小马甲应助冷静映寒采纳,获得10
9秒前
明亮的嚣完成签到,获得积分10
10秒前
putaoyou34发布了新的文献求助20
11秒前
深情安青应助典雅的悟空采纳,获得10
11秒前
英俊的铭应助1035646426采纳,获得10
11秒前
13秒前
英姑应助请叫我过儿采纳,获得10
13秒前
xxlhp完成签到,获得积分10
14秒前
仇晓煜发布了新的文献求助10
15秒前
槿言完成签到 ,获得积分10
15秒前
16秒前
Fe发布了新的文献求助10
17秒前
17秒前
18秒前
沉舟发布了新的文献求助10
18秒前
19秒前
22秒前
23秒前
24秒前
24秒前
莫白完成签到,获得积分10
25秒前
25秒前
Moonpie完成签到,获得积分0
26秒前
molihuakai应助cqnusq采纳,获得10
27秒前
27秒前
ding应助活力的母鸡采纳,获得10
27秒前
KK发布了新的文献求助10
28秒前
kuiuLinvk完成签到,获得积分10
28秒前
28秒前
科研通AI6.2应助简单千琴采纳,获得10
29秒前
无私迎海发布了新的文献求助10
29秒前
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
模型平均及其应用 900
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 550
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7336204
求助须知:如何正确求助?哪些是违规求助? 8950050
关于积分的说明 18992480
捐赠科研通 6989626
什么是DOI,文献DOI怎么找? 3217808
关于科研通互助平台的介绍 2383861
邀请新用户注册赠送积分活动 2197876