Credentialing features: a platform to benchmark and optimize untargeted metabolomic methods.
Credentialing features: a platform to benchmark and optimize untargeted metabolomic methods.
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DOI：
10.1021/ac503092d
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发表时间：
2014-10-07
影响因子：
7.4
通讯作者：
Patti, Gary J.
中科院分区：
文献类型：
--
作者：
Mahieu, Nathaniel Guy;Huang, Xiaojing;Chen, Ying-Jr;Patti, Gary J.
非靶向代谢组学的目的是描述尽可能多的代谢物，然而一个主要的挑战是在代谢组覆盖的基础上比较实验方法的性能。到目前为止，大多数已发表的方法都是通过计算检测到的特征总数来比较实验方法。然而，由于人为干扰，这个数字是高度可变的，因此不是比较代谢组学方法的一个很差的指标。在这里，我们介绍了另一种基准代谢组覆盖率的方法，该方法依赖于在常规和富含13C的培养液中培养的细胞的混合大肠杆菌提取物。在对这些提取物进行基于质谱学的代谢组学分析后，我们根据同位素间距和强度确定了来自大肠杆菌代谢物的特征。这个认证平台使我们能够准确地比较不同实验方法产生的非人工特征的数量。我们通过重新优化已发表的用于XCMS数据处理的非靶向代谢组学方法，突出了我们平台的价值。与已公布的参数相比，新的XCMS参数将特征总数减少了15%(噪声特征减少)，而检测到的真实代谢物和分组的数量增加了20%。我们的认证平台依赖于容易生成的大肠杆菌样本和一个简单的软件算法，该算法可以在我们的实验室网站上免费获得()。我们已经使用反相和亲水相互作用液相色谱以及Agilent、Thermo Science、AB SCIEX和LECO质谱仪验证了认证平台。因此，认证平台可以很容易地被任何实验室应用，以优化其用于代谢物提取、层析分离、质谱学检测和生物信息处理的非靶向代谢物流水线。
The aim of untargeted metabolomics is to profile as many metabolites as possible, yet a major challenge is comparing experimental method performance on the basis of metabolome coverage. To date, most published approaches have compared experimental methods by counting the total number of features detected. Due to artifactual interference, however, this number is highly variable and therefore is a poor metric for comparing metabolomic methods. Here we introduce an alternative approach to benchmarking metabolome coverage which relies on mixed Escherichia coli extracts from cells cultured in regular and 13C-enriched media. After mass spectrometry-based metabolomic analysis of these extracts, we “credential” features arising from E. coli metabolites on the basis of isotope spacing and intensity. This credentialing platform enables us to accurately compare the number of nonartifactual features yielded by different experimental approaches. We highlight the value of our platform by reoptimizing a published untargeted metabolomic method for XCMS data processing. Compared to the published parameters, the new XCMS parameters decrease the total number of features by 15% (a reduction in noise features) while increasing the number of true metabolites detected and grouped by 20%. Our credentialing platform relies on easily generated E. coli samples and a simple software algorithm that is freely available on our laboratory Web site (). We have validated the credentialing platform with reversed-phase and hydrophilic interaction liquid chromatography as well as Agilent, Thermo Scientific, AB SCIEX, and LECO mass spectrometers. Thus, the credentialing platform can readily be applied by any laboratory to optimize their untargeted metabolomic pipeline for metabolite extraction, chromatographic separation, mass spectrometric detection, and bioinformatic processing.
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DOI：
10.1056/nejmoa1109400
发表时间：
2013-04-25
期刊：
The New England journal of medicine
影响因子：
--
作者：
Tang WH;Wang Z;Levison BS;Koeth RA;Britt EB;Fu X;Wu Y;Hazen SL
通讯作者：
Hazen SL
影响因子：
48
作者：
Hebert, Alexander S.;Merrill, Anna E.;Bailey, Derek J.;Still, Amelia J.;Westphall, Michael S.;Strieter, Eric R.;Pagliarini, David J.;Coon, Joshua J.
通讯作者：
Coon, Joshua J.
影响因子：
7.4
作者：
Stupp, Gregory S.;Clendinen, Chaevien S.;Ajredini, Ramadan;Szewc, Mark A.;Garret, Timothy;Menger, Robert F.;Yost, Richard A.;Beecher, Chris;Edison, Arthur S.
通讯作者：
Edison, Arthur S.
影响因子：
7.4
作者：
Masson, Perrine;Alves, Alexessander Couto;Want, Elizabeth J.
通讯作者：
Want, Elizabeth J.
DOI：
10.1016/j.jchromb.2008.04.031
发表时间：
2008-08-15
影响因子：
3
作者：
Lu, Wenyun;Bennett, Bryson D.;Rabinowitz, Joshua D.
通讯作者：
Rabinowitz, Joshua D.