MagMet: A fully automated web server for targeted nuclear magnetic resonance metabolomics of plasma and serum

IF 1.9 3区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY
Manoj Rout, Matthias Lipfert, Brian L. Lee, Mark Berjanskii, Nazanin Assempour, Rosa Vazquez Fresno, Arnau Serra Cayuela, Ying Dong, Mathew Johnson, Honeya Shahin, Vasuk Gautam, Tanvir Sajed, Eponine Oler, Harrison Peters, Rupasri Mandal, David S. Wishart
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引用次数: 1

Abstract

Nuclear magnetic resonance (NMR) spectral analysis of biofluids can be a time-consuming process, requiring the expertise of a trained operator. With NMR becoming increasingly popular in the field of metabolomics, there is a growing need to change this paradigm and to automate the process. Here we introduce MagMet, an online web server, that automates the processing and quantification of 1D 1H NMR spectra from biofluids—specifically, human serum/plasma metabolites, including those associated with inborn errors of metabolism (IEM). MagMet uses a highly efficient data processing procedure that performs automatic Fourier Transformation, phase correction, baseline optimization, chemical shift referencing, water signal removal, and peak picking/peak alignment. MagMet then uses the peak positions, linewidth information, and J-couplings from its own specially prepared standard metabolite reference spectral NMR library of 85 serum/plasma compounds to identify and quantify compounds from experimentally acquired NMR spectra of serum/plasma. MagMet employs linewidth adjustment for more consistent quantification of metabolites from higher field instruments and incorporates a highly efficient data processing procedure for more rapid and accurate detection and quantification of metabolites. This optimized algorithm allows the MagMet webserver to quickly detect and quantify 58 serum/plasma metabolites in 2.6 min per spectrum (when processing a dataset of 50–100 spectra). MagMet's performance was also assessed using spectra collected from defined mixtures (simulating other biofluids), with >100 previously measured plasma spectra, and from spiked serum/plasma samples simulating known IEMs. In all cases, MagMet performed with precision and accuracy matching the performance of human spectral profiling experts. MagMet is available at http://magmet.ca.

Abstract Image

MagMet:针对血浆和血清的核磁共振代谢组学的全自动web服务器。
生物流体的核磁共振(NMR)光谱分析可能是一个耗时的过程,需要训练有素的操作人员的专业知识。随着核磁共振在代谢组学领域的日益普及,越来越需要改变这种模式并使该过程自动化。在这里,我们介绍MagMet,一个在线web服务器,可以自动处理和定量生物体液的1D 1h NMR谱,特别是人类血清/血浆代谢物,包括那些与先天性代谢错误(IEM)相关的代谢物。MagMet使用高效的数据处理程序,可执行自动傅里叶变换、相位校正、基线优化、化学位移参考、水信号去除和峰值拾取/峰值对齐。然后,MagMet利用其专门制备的85种血清/血浆化合物的标准代谢物参考光谱核磁共振库中的峰位置、线宽信息和j偶联,从实验获得的血清/血浆核磁共振光谱中鉴定和定量化合物。MagMet采用线宽调整,从更高的现场仪器中获得更一致的代谢物定量,并结合高效的数据处理程序,实现更快速、更准确的代谢物检测和定量。该优化算法允许MagMet网络服务器在2.6分钟内快速检测和量化58个血清/血浆代谢物(当处理50-100个光谱的数据集时)。MagMet的性能还通过从确定的混合物(模拟其他生物流体)收集的光谱、bbb100先前测量的血浆光谱以及模拟已知IEMs的加标血清/血浆样品来评估。在所有情况下,MagMet的执行精度和准确性与人类光谱分析专家的性能相匹配。MagMet可以在http://magmet.ca上找到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.70
自引率
10.00%
发文量
99
审稿时长
1 months
期刊介绍: MRC is devoted to the rapid publication of papers which are concerned with the development of magnetic resonance techniques, or in which the application of such techniques plays a pivotal part. Contributions from scientists working in all areas of NMR, ESR and NQR are invited, and papers describing applications in all branches of chemistry, structural biology and materials chemistry are published. The journal is of particular interest not only to scientists working in academic research, but also those working in commercial organisations who need to keep up-to-date with the latest practical applications of magnetic resonance techniques.
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